Laboratoire de l Informatique du Parallélisme

Size: px
Start display at page:

Download "Laboratoire de l Informatique du Parallélisme"

Transcription

1 Laboratoire de l Informatique du Parallélisme Ecole Normale Suérieure de Lyon Unité de recherche associée au CNRS n 1398 Asynchronous Sub-Logarithmic Adders J.M. Muller, A. Tisserand and J.M. Vincent May 16, 1997 Research Reort N o RR Ecole Normale Suérieure de Lyon 46 Allée d Italie, Lyon Cedex 7, France Téléhone : (+33) () Télécoieur : (+33) () Adresse électronique : li@li.ens lyon.fr

2 Asynchronous Sub-Logarithmic Adders J.M. Muller, A. Tisserand and J.M. Vincent May 16, 1997 Abstract Fast arithmetic oerators have always been an imortant toic in comuter design. There are two kinds of arithmetic oerators: xed-time and variable-time ones. While xed-time arithmetic oerators have been widely studied, variable-time oerators seem to be more and more interesting for low-ower design and very high erformance comuting. Self-timed arithmetic oerators are able to deliver their result in an average comutation time less than the worst case time. We resent an architecture, which is a variant of the carry select adder, for the addition of n-bit numbers with a O( log 2 n) average comutation time. Keywords: Comuter arithmetic, asynchronous oerators, addition Resume La concetion d'oerateurs arithmetiques raides est un enjeu imortant dans la realisation d'un ordinateur. Il existe deux tyes d'oerateurs arithmetiques : ceux a delai xe et ceux a delai variable. Tandis que les oerateurs a delai xe ont ete beaucou etudies dans le asse, les oerateurs a delai variable semblent tres rometteurs our les realisations basse consommation et our le calcul haute erformance. Les oerateurs auto-sequences delivrent leur resultat dans un tems moyen beaucou lus etit que le tems dans le ire cas. Nous resentons ici une nouvelle architecture, basee sur l'additionneur a selection de la retenue, our laquelle le tems moyen d'une addition de deux nombres de n chires est en O( log 2 n). Mots-cles: Arithmetique des ordinateurs, oerateurs asynchrones, addition

3 Asynchronous Sub-Logarithmic Adders Jean-Michel Muller and Arnaud Tisserand CNRS, Laboratoire LIP ENS Lyon. 46 Allee d'italie LYON Cedex 7, FRANCE Jean-Marc Vincent Laboratoire LMC - IMAG. 1 rue des Mathematiques, BP GRENOBLE Cedex 9, FRANCE Jean-Marc.Vincent@imag.fr Abstract Fast arithmetic oerators have always been an imortant toic in comuter design. There are two kinds of arithmetic oerators: xed-time and variabletime ones. While xed-time arithmetic oerators have been widely studied, variable-time oerators seem to be more and more interesting for low-ower design and very high erformance comuting. Self-timed arithmetic oerators are able to deliver their result in an average comutation time less than the worst case time. We resent an architecture, which is a variant of the carry select adder, for the addition of n-bit numbers with a O( log 2 n) average comutation time. 1 Introduction Fast arithmetic oerators have always been a main goal in comuter design. There are two kinds of arithmetic oerators: xed-time and variable-time ones. Fixed-time oerators for the basic arithmetic oerations (addition, multilication, division and square-root) have been widely studied ([Kor93], [Omo94]). Variable-time oerators are able to erform very fast comutations whose based on algorithms for which the average comutation time is signicantly dierent from the worst case comutation time. In most arithmetic oerations the average comutation time is less than the worst case comutation time. Self-timed oerators can be used in low-ower alications such as mobile systems ([BBK + 94]). In asynchronous oerators there is no exensive global clock signal which roduces an amount of current at each clock edge. Another use of self-timed oerators is the design of reliable circuits and variable bandwidth systems. Indeed, self-timed oerators are able to achieve their comutations in a large interval of electrical arameters such as suly voltage ([RRPB96]). The design of self-timed oerators is dierent from the design of synchronous oerators both from the theoretical and imlementation oints of view. Due to the asynchronous imlementation, only the real change of signal state must be detected ([Hau95]). But the imlementation is not the only dierence between synchronous and asynchronous oerator design: there may also be algorithmic dierences. One reason is that the minimization of the average comutation time and the minimization of the worst case comutation time do not lead to the same results. An imortant characteristic of asynchronous oerators is the need to detect of the com-

4 letion of the comutation. In order to send its result to the next oerators, an oerator must in general rovide a comletion detection signal. There are a few excetions to this rule: alications for which having from time to time a slightly erroneous result is accetable, rovided that the robability of error is small enough (secic alications in signal and image rocessing, some data comression algorithms, some neural networks algorithms... ). In this aer we deal with fast asynchronous arithmetic algorithms and architectures for the addition, and their hardware imlementation. We use the robability distribution of the comutation time as a tool to erform analysis and comarisons of dierent addition algorithms. In the rst art we recall the average comutation time and we give some informations about the robability distribution of the comutation time for the simlest adder: the rile carry adder. The average comutation time of the rile carry adder have been given in many aers (see [BGN47] for examle). But the average comutation time does not suce to chose between several algorithms. Indeed, we need the robability distribution of the comutation time in order to design oerators for very fast alications allowing a very small error, rovided that the robability of this error is small enough. In the second art we resent an asynchronous adder, its architecture and its analysis. This adder, based on a modication of the carry select adder, has a sub-logarithmic average comutation time, more recisely O( log 2 n) (n-bit oerands). We also analyze dierent comletion schemes with a small hardware overhead for this adder. 2 The Rile Carry Adder In this aer we deal with n bit integers reresented in the usual binary system (the results for the 2's comlement notation are obviously similar): A = (a n?1a n?2 : : : a 1 a ) = n?1 X i= a i 2 i : Brent ([Bre7]) and Winograd([Win65]) have shown that the time comlexity of the binary addition in the synchronous case is O(log 2 n) rovided that we use gates with bounded fan-in and fan-out. The rile carry adder () is the direct transcrition of the aer-and-encil algorithm (see gure 1). Each cell is a full-adder (FA) that comutes the sum b n?1 a n?1 b n?2 a n?2 b 1 a 1 b a c n c n?1 c n?2 c 2 c 1 c F A n?1 F A n?2 F A 1 F A s n?1 s n?2 s 1 s Figure 1: A n-bit Rile Carry Adder bit s i and the carry out bit c i+1 from the two oerands inut bits (a i ; b i ) and the carry-in bit c i using the well-known formul: s i = a i b i c i c i+1 = (a i ^ b i ) _ (a i ^ c i ) _ (b i ^ c i ): The average comutation time (ACT) of the rile carry adder is O(log 2 n) (see gure 2). This result was shown by Burks, Goldstine and Von Neumann in [BGN47].

5 1 8 7 Average Comutation Oerand Size (bits) Figure 2: The Average Comutation Time of several Rile Carry Adders (4 n 128) The average comutation time (ACT) is not the only interesting characteristics of an asynchronous arithmetic oerator. The comutation time robability distribution (CTPD) is a good information to comare oerators. We resent in gure 3 the comutation time distribution for s of 32 and 128 binary digits. The time unit is the delay of a full-adder cell. We have erformed a comlete analysis of the robabilistic characteristic of the rile carry adder using generating functions. The gures 3 and 2 are deduced from this analysis digit 128-digit E-2 Probabilty.15 1E-2 Probabilty.1 1E-3.1 1E-3.5 1E-6.5 1E Figure 3: Comutation Time Probability Distribution for 32 and 128-bit Rile Carry Adders We can see on the CTPD curves (gure 3) that most cases time a n-bit addition is comleted much before the time n (where is the time of one full adder cell). From the robabilistic analysis of the rile carry adder we can calculate the robability that an n-bit addition is not nished at time t for any t in the interval [; n ]. For examle, with a 128-bit adder the robability that the addition is not comlete at the time 32 is 2:28 1?8. Figure 4 resents the robability failure for rile carry adders with 16, 32, 64 and 128 bits. This can be eciently used in some alications for which having a slightly erroneous result with a low robability is accetable (secic alications in signal and image rocessing, no-exact data comression algorithms, some neural networks algorithms... ).

6 1e bits 32 bits 64 bits 128 bits 1e-1 Failure Probability 1e-2 1e Figure 4: Failure robability as a function of the stoing time for a n bits rile carry adder 3 The Sub-Logarithmic Carry Select Adder In this section we resent an adder called sub-logarithmic carry select adder () which average comutation time is O( log 2 n). This adder is based on a modication of the well-known carry select adder. The sub-logarithmic carry select adder is based on the following rinciles: a carry anticiation strategy, an asynchronous carry roagation scheme. 3.1 The Sub-Logarithmic Carry Select Adder Architecture The whole architecture of the sub-logarithmic carry select adder is resented gure 5 and the basic cell is resented gure 6. The basic cell is made u with two -bit A n B n A n B n?1?1 A 2 B 2 A 1 B 1 S n S n?1 S 2 S 1 Figure 5: The Sub-Logarithmic Carry Select Adder rile carry adders. The two inut n-bit numbers (A; B) are slit into small blocks of bits (A = A n= : : : A 2 A 1 and A k = a (k?1)a (k?1)+1 : : : a (k?1)+?1; 8k 2 [1:: n], the same for B and S). Each basic cell of the receives two inut blocks (A k ; B k ) and roduces one block of the sum S k. The carry anticiation scheme is the same as in carry select adders. One adder is fed with an inut carry equal to while the second adder is fed with an inut carry equal to 1. The carry-in block signal c in connects the outut corresonding to the sum of the whole block with the sum outut of the adder which had the good anticiated inut carry. In the following we assume that n is an integer. In ractice, if n is not an integer we can adjust the size of the last block with a block size smaller than. We will see in the next section what value is convenient for. In n-bit conditional sum adders, 3 adders of size n=2 are used. The rst comutes the sum of the n=2 least signicant digits while the two other adders comute the

7 A k B k -digit 1 d 1 one bit wire wires c out 1 S k c in Figure 6: The Sub-Logarithmic Carry Select Adder Cell sum of the half most signicant digits, one with an inut carry equal to and the second with an inut carry equal to 1. These 3 sums can be erformed in a fully arallel scheme. When the rst adder has a result it is ossible to determine which result of the two other adders should be used. This strategy is alied in a recursive way, then conditional sum adders have a comutation time equal to O(log 2 n). 3.2 Evaluation In this subsection we give the analysis of the sub-logarithmic carry select adder that shows the average and the worst case comutation time. We resent the comutation time robability distribution of the using simulations Analysis During a rst \ste" all the basic cells of the comute their results in arallel. After this comutation, there is a roagation of the carry c out of each block. There is an imortant overlaing of these two \stes" due to the asynchronous scheme. Each block has an average comutation time equal to the average comutation time of a -bit adder lus a constant time due to the multilexer erforming the choice between the oututs of the two adders (in this analysis we neglect this constant time). As we have shown in section 2, the average comutation time for a n-bit rile carry adder is O(log 2 n). In order to make sure that in all blocks the comutation time is less than O(log 2 n) we must have < log 2 n. In the following we use a time unit equal to the delay of one full-adder cell. The worst case comutation time is for one basic cell. The average time needed for the comletion of all the basic cells is slightly less than. Indeed, for one basic cell the average comutation time is O(log 2 ), but for all the n basic cells the robability that there is at least a roagation all over one cell is high since < log 2 n. Hence, the average comutation time for the comletion of all basic cells is bounded by k 1, with k 1 slightly less than 1. The worst case comutation time for the roagation of the block carries is the time needed by the signal to ass through n multilexers. Let k 2 be the time necessary to ass through the multilexer which erforms the choice between the inut block carry c in and the anticiated carry in each basic cell (with the time unit equal to the delay of one full-adder cell, k 2 is much less than 1). Then the worst case comutation time for the is:

8 + k 2 n : We have seen above that the average comutation time for the comletion of all basic cells can be uer bounded by k 1 with k 1 slightly less than 1. The average comutation time for the roagation of the block carries is log 2 n, because it is equal to the average carry length in the whole adder (that is log 2 n) divided by the size of the block (that is ). The average comutation time of the sub-logarithmic carry select adder T is: T f(n) = k 1 + log 2 k 2 n : q k2 The function f(n) is minimal for = log k1 2 n. For this value of the average comutation time of the is 2 k 1 k 2 log 2 n. Then we have the comlexity of the sub-logarithmic carry select adder: T = O( log 2 n): The area used by a n-bit sub-logarithmic carry select adder is more than two times the area of a rile carry adder. In ractice the best choice for the value of deends on the value of the technological constants k 1 and k 2. In [GO96], De Gloria and Olivieri have built a fast asynchronous adder based on statistical carry lookahead adders (SCLA). This adder has an average comutation time less than O(log 2 n) but our simulation results (see section 3.2.2) shows that our adder is faster. The areas needed by both adders are close together. The oint that makes the simler to imlement is the fan-in, all the gates in the have a bounded fan-in while in the SCLA some gates have a non-bounded fan-in Simulations In this art of the aer we erform some comarisons between our sub-logarithmic carry select adder and the rile carry adder using simulations. Figure 7 resent comarisons between the average comutation time of the and the for several block sizes. The curves are reresented with lain lines and curves with dotted lines. Our simulations are such that the condence interval of the results have a length smaller than 1?6. The following table gives some values for the average comutation time of the sublogarithmic carry select adder and for the rile carry adder. In this table we can see that with blocks of size 2 is very ecient for small adders and a with blocks of size 3 is a good choice for large adders. The time unit used in these simulations is the delay of one full-adder cell. adder sizes block sizes

9 Average Comutation Average Comutation Oerand Size (bits) Block size Oerand Size (bits) Block size Average Comutation Average Comutation Oerand Size (bits) Oerand Size (bits) Block size 6 Block size 8 Figure 7: Comarisons between the average comutation time of the sublogarithmic carry select adder and the rile carry adder In gure 8 the comutation time robability distribution of 128-bit sub-logarithmic carry select adders of dierent block sizes are comared with the 128-bit rile carry adder. As with rile carry the comutation time robability distribution is useful for determining the time after which we can sto the comutation for secial alications. On the dierent curves we can see that the stoing time of the is smaller than the stoing time of the. 3.3 Comletion detection in the In this last section we deal with the comletion detection in the sub-logarithmic carry select adder. The comletion detection is a critical oint in asynchronous systems. Usually, the comletion detection is based on delay-insensitive codes such as double-rail code (see [Ver88] for more information on delay-insensitive codes). Such codes give reliable circuits but their area is rather large. In the, we can use an economical (in term of area) comletion detection strategy. We have shown in section that in most cases there is a least one basic cell on which there is a carry roagation all over this cell. It is not that dicult to build a comletion detection which tends to determinate when all the basic cells have nished their comutation. As in most cases the comutation of all basic cells is comlete after a time close to times the delay of one full-adder cell, we should start the comletion detection after this time. Then we just need to detect when all the block carries (c out is gure 6) have comleted their roagation. This can be done using a double-rail code with a very small chi area.

10 Probability.4 Probability Block size Block size Probability.4 Probability Block size 6 Block size 8 Figure 8: Sub-logarithmic carry select adder comutation time distribution 4 Conclusion In this aer we have shown a new fast asynchronous adder whose average comutation time is O( log 2 n) called sub-logarithmic carry select adder (). The worst case comutation time of the is also smaller than the worst case comutation time of the rile carry adder. We have also resented a comletion detection solution for this adder allowing ecient VLSI imlementations of large adders. In this aer we use the robabilities and esecially the comutation time robability distribution as a owerful tool for erforming comarisons between several asynchronous arithmetic algorithms. In future works we will study self-timed oerators for multilication and division. References [BBK + 94] K. Van Berkel, R. Burgess, J. Kessels, M. Roncken, F. Schalij, and A. Peeters. Asynchronous circuits for low ower: A DCC error corrector. IEEE Design and Test of Comuters, 11(2):22{32, June [BGN47] [Bre7] [GO96] A.W. Burks, H.H. Goldstine, and J. Von Neumann. Preliminary discusion of the logical design of an electronic instrument. Technical reort, The Institut of Advanced Study, Princeton, N.J., (rerinted in Bell and Newell, Comuter structures: readings and examles, Comuter Science series, Mc Graw-Hill, 1971). R.P. Brent. On the addition of binary numbers. IEEE Transactions on Comuters, ages 758{759, August 197. A. De Gloria and M. Olivieri. Statistical carry lookahead adders. IEEE Transactions on Comuters, 45(3):34{347, March 1996.

11 [Hau95] S. Hauck. Asynchronous design methodologies: An overview. Proceedings of the IEEE, 83(1):69{93, January [Kor93] I. Koren. Comuter Arithmetic Algorithms. Prentice-Hall, [Omo94] A.R. Omondi. Comuter Arithmetic Systems. Algorithms, Architecture and Imlementations. Prentice-Hall, [RRPB96] F. Robin, M. Renaudin, G. Privat, and N. Van Den Bossche. A functionally asynchronous array-rocessor for morhological ltering of greysacle images. IEE Comuters and Digital Techniques, July Secial Issue on Asynchronous Processors. [Ver88] [Win65] T. Verhoe. Delay-insensitive codes - an overview. Distributed Comuting, 3:1{8, S. Winograd. On the time required to erform addition. Journal of the Association for Comuting Machinery, 12(2):277{285, Aril 1965.

Computer arithmetic. Intensive Computation. Annalisa Massini 2017/2018

Computer arithmetic. Intensive Computation. Annalisa Massini 2017/2018 Comuter arithmetic Intensive Comutation Annalisa Massini 7/8 Intensive Comutation - 7/8 References Comuter Architecture - A Quantitative Aroach Hennessy Patterson Aendix J Intensive Comutation - 7/8 3

More information

Laboratoire de l Informatique du Parallélisme. École Normale Supérieure de Lyon Unité Mixte de Recherche CNRS-INRIA-ENS LYON n o 8512

Laboratoire de l Informatique du Parallélisme. École Normale Supérieure de Lyon Unité Mixte de Recherche CNRS-INRIA-ENS LYON n o 8512 Laboratoire de l Informatique du Parallélisme École Normale Supérieure de Lyon Unité Mixte de Recherche CNRS-INRIA-ENS LYON n o 8512 SPI A few results on table-based methods Jean-Michel Muller October

More information

RN-coding of numbers: definition and some properties

RN-coding of numbers: definition and some properties Laboratoire de l Informatique du Parallélisme École Normale Supérieure de Lyon Unité Mixte de Recherche CNRS-INRIA-ENS LYON-UCBL n o 5668 RN-coding of numbers: definition and some properties Peter Kornerup,

More information

Laboratoire de l Informatique du Parallélisme

Laboratoire de l Informatique du Parallélisme Laboratoire de l Informatique du Parallélisme Ecole Normale Supérieure de Lyon Unité de recherche associée au CNRS n 1398 An Algorithm that Computes a Lower Bound on the Distance Between a Segment and

More information

Characterizing the Behavior of a Probabilistic CMOS Switch Through Analytical Models and Its Verification Through Simulations

Characterizing the Behavior of a Probabilistic CMOS Switch Through Analytical Models and Its Verification Through Simulations Characterizing the Behavior of a Probabilistic CMOS Switch Through Analytical Models and Its Verification Through Simulations PINAR KORKMAZ, BILGE E. S. AKGUL and KRISHNA V. PALEM Georgia Institute of

More information

Elliptic Curves and Cryptography

Elliptic Curves and Cryptography Ellitic Curves and Crytograhy Background in Ellitic Curves We'll now turn to the fascinating theory of ellitic curves. For simlicity, we'll restrict our discussion to ellitic curves over Z, where is a

More information

Round-off Errors and Computer Arithmetic - (1.2)

Round-off Errors and Computer Arithmetic - (1.2) Round-off Errors and Comuter Arithmetic - (.). Round-off Errors: Round-off errors is roduced when a calculator or comuter is used to erform real number calculations. That is because the arithmetic erformed

More information

John Weatherwax. Analysis of Parallel Depth First Search Algorithms

John Weatherwax. Analysis of Parallel Depth First Search Algorithms Sulementary Discussions and Solutions to Selected Problems in: Introduction to Parallel Comuting by Viin Kumar, Ananth Grama, Anshul Guta, & George Karyis John Weatherwax Chater 8 Analysis of Parallel

More information

Unit 1 - Computer Arithmetic

Unit 1 - Computer Arithmetic FIXD-POINT (FX) ARITHMTIC Unit 1 - Comuter Arithmetic INTGR NUMBRS n bit number: b n 1 b n 2 b 0 Decimal Value Range of values UNSIGND n 1 SIGND D = b i 2 i D = 2 n 1 b n 1 + b i 2 i n 2 i=0 i=0 [0, 2

More information

For q 0; 1; : : : ; `? 1, we have m 0; 1; : : : ; q? 1. The set fh j(x) : j 0; 1; ; : : : ; `? 1g forms a basis for the tness functions dened on the i

For q 0; 1; : : : ; `? 1, we have m 0; 1; : : : ; q? 1. The set fh j(x) : j 0; 1; ; : : : ; `? 1g forms a basis for the tness functions dened on the i Comuting with Haar Functions Sami Khuri Deartment of Mathematics and Comuter Science San Jose State University One Washington Square San Jose, CA 9519-0103, USA khuri@juiter.sjsu.edu Fax: (40)94-500 Keywords:

More information

MATHEMATICAL MODELLING OF THE WIRELESS COMMUNICATION NETWORK

MATHEMATICAL MODELLING OF THE WIRELESS COMMUNICATION NETWORK Comuter Modelling and ew Technologies, 5, Vol.9, o., 3-39 Transort and Telecommunication Institute, Lomonosov, LV-9, Riga, Latvia MATHEMATICAL MODELLIG OF THE WIRELESS COMMUICATIO ETWORK M. KOPEETSK Deartment

More information

Evaluating Circuit Reliability Under Probabilistic Gate-Level Fault Models

Evaluating Circuit Reliability Under Probabilistic Gate-Level Fault Models Evaluating Circuit Reliability Under Probabilistic Gate-Level Fault Models Ketan N. Patel, Igor L. Markov and John P. Hayes University of Michigan, Ann Arbor 48109-2122 {knatel,imarkov,jhayes}@eecs.umich.edu

More information

2 K. ENTACHER 2 Generalized Haar function systems In the following we x an arbitrary integer base b 2. For the notations and denitions of generalized

2 K. ENTACHER 2 Generalized Haar function systems In the following we x an arbitrary integer base b 2. For the notations and denitions of generalized BIT 38 :2 (998), 283{292. QUASI-MONTE CARLO METHODS FOR NUMERICAL INTEGRATION OF MULTIVARIATE HAAR SERIES II KARL ENTACHER y Deartment of Mathematics, University of Salzburg, Hellbrunnerstr. 34 A-52 Salzburg,

More information

The Graph Accessibility Problem and the Universality of the Collision CRCW Conflict Resolution Rule

The Graph Accessibility Problem and the Universality of the Collision CRCW Conflict Resolution Rule The Grah Accessibility Problem and the Universality of the Collision CRCW Conflict Resolution Rule STEFAN D. BRUDA Deartment of Comuter Science Bisho s University Lennoxville, Quebec J1M 1Z7 CANADA bruda@cs.ubishos.ca

More information

GIVEN an input sequence x 0,..., x n 1 and the

GIVEN an input sequence x 0,..., x n 1 and the 1 Running Max/Min Filters using 1 + o(1) Comarisons er Samle Hao Yuan, Member, IEEE, and Mikhail J. Atallah, Fellow, IEEE Abstract A running max (or min) filter asks for the maximum or (minimum) elements

More information

On the Toppling of a Sand Pile

On the Toppling of a Sand Pile Discrete Mathematics and Theoretical Comuter Science Proceedings AA (DM-CCG), 2001, 275 286 On the Toling of a Sand Pile Jean-Christohe Novelli 1 and Dominique Rossin 2 1 CNRS, LIFL, Bâtiment M3, Université

More information

MODULAR LINEAR TRANSVERSE FLUX RELUCTANCE MOTORS

MODULAR LINEAR TRANSVERSE FLUX RELUCTANCE MOTORS MODULAR LINEAR TRANSVERSE FLUX RELUCTANCE MOTORS Dan-Cristian POPA, Vasile IANCU, Loránd SZABÓ, Deartment of Electrical Machines, Technical University of Cluj-Naoca RO-400020 Cluj-Naoca, Romania; e-mail:

More information

Outline. EECS150 - Digital Design Lecture 26 Error Correction Codes, Linear Feedback Shift Registers (LFSRs) Simple Error Detection Coding

Outline. EECS150 - Digital Design Lecture 26 Error Correction Codes, Linear Feedback Shift Registers (LFSRs) Simple Error Detection Coding Outline EECS150 - Digital Design Lecture 26 Error Correction Codes, Linear Feedback Shift Registers (LFSRs) Error detection using arity Hamming code for error detection/correction Linear Feedback Shift

More information

Parallel Quantum-inspired Genetic Algorithm for Combinatorial Optimization Problem

Parallel Quantum-inspired Genetic Algorithm for Combinatorial Optimization Problem Parallel Quantum-insired Genetic Algorithm for Combinatorial Otimization Problem Kuk-Hyun Han Kui-Hong Park Chi-Ho Lee Jong-Hwan Kim Det. of Electrical Engineering and Comuter Science, Korea Advanced Institute

More information

MODELING THE RELIABILITY OF C4ISR SYSTEMS HARDWARE/SOFTWARE COMPONENTS USING AN IMPROVED MARKOV MODEL

MODELING THE RELIABILITY OF C4ISR SYSTEMS HARDWARE/SOFTWARE COMPONENTS USING AN IMPROVED MARKOV MODEL Technical Sciences and Alied Mathematics MODELING THE RELIABILITY OF CISR SYSTEMS HARDWARE/SOFTWARE COMPONENTS USING AN IMPROVED MARKOV MODEL Cezar VASILESCU Regional Deartment of Defense Resources Management

More information

Feedback-error control

Feedback-error control Chater 4 Feedback-error control 4.1 Introduction This chater exlains the feedback-error (FBE) control scheme originally described by Kawato [, 87, 8]. FBE is a widely used neural network based controller

More information

1 1 c (a) 1 (b) 1 Figure 1: (a) First ath followed by salesman in the stris method. (b) Alternative ath. 4. D = distance travelled closing the loo. Th

1 1 c (a) 1 (b) 1 Figure 1: (a) First ath followed by salesman in the stris method. (b) Alternative ath. 4. D = distance travelled closing the loo. Th 18.415/6.854 Advanced Algorithms ovember 7, 1996 Euclidean TSP (art I) Lecturer: Michel X. Goemans MIT These notes are based on scribe notes by Marios Paaefthymiou and Mike Klugerman. 1 Euclidean TSP Consider

More information

Distributed Rule-Based Inference in the Presence of Redundant Information

Distributed Rule-Based Inference in the Presence of Redundant Information istribution Statement : roved for ublic release; distribution is unlimited. istributed Rule-ased Inference in the Presence of Redundant Information June 8, 004 William J. Farrell III Lockheed Martin dvanced

More information

Multi-Operation Multi-Machine Scheduling

Multi-Operation Multi-Machine Scheduling Multi-Oeration Multi-Machine Scheduling Weizhen Mao he College of William and Mary, Williamsburg VA 3185, USA Abstract. In the multi-oeration scheduling that arises in industrial engineering, each job

More information

Universal Finite Memory Coding of Binary Sequences

Universal Finite Memory Coding of Binary Sequences Deartment of Electrical Engineering Systems Universal Finite Memory Coding of Binary Sequences Thesis submitted towards the degree of Master of Science in Electrical and Electronic Engineering in Tel-Aviv

More information

Topic: Lower Bounds on Randomized Algorithms Date: September 22, 2004 Scribe: Srinath Sridhar

Topic: Lower Bounds on Randomized Algorithms Date: September 22, 2004 Scribe: Srinath Sridhar 15-859(M): Randomized Algorithms Lecturer: Anuam Guta Toic: Lower Bounds on Randomized Algorithms Date: Setember 22, 2004 Scribe: Srinath Sridhar 4.1 Introduction In this lecture, we will first consider

More information

VLSI Design Issues. ECE 410, Prof. F. Salem/Prof. A. Mason notes update

VLSI Design Issues. ECE 410, Prof. F. Salem/Prof. A. Mason notes update VLSI Design Issues Scaling/Moore s Law has limits due to the hysics of material. Now L (L=20nm??) affects tx delays (seed), noise, heat (ower consumtion) Scaling increases density of txs and requires more

More information

A Parallel Algorithm for Minimization of Finite Automata

A Parallel Algorithm for Minimization of Finite Automata A Parallel Algorithm for Minimization of Finite Automata B. Ravikumar X. Xiong Deartment of Comuter Science University of Rhode Island Kingston, RI 02881 E-mail: fravi,xiongg@cs.uri.edu Abstract In this

More information

Catalan s Equation Has No New Solution with Either Exponent Less Than 10651

Catalan s Equation Has No New Solution with Either Exponent Less Than 10651 Catalan s Euation Has No New Solution with Either Exonent Less Than 065 Maurice Mignotte and Yves Roy CONTENTS. Introduction and Overview. Bounding One Exonent as a Function of the Other 3. An Alication

More information

Radial Basis Function Networks: Algorithms

Radial Basis Function Networks: Algorithms Radial Basis Function Networks: Algorithms Introduction to Neural Networks : Lecture 13 John A. Bullinaria, 2004 1. The RBF Maing 2. The RBF Network Architecture 3. Comutational Power of RBF Networks 4.

More information

A MIXED CONTROL CHART ADAPTED TO THE TRUNCATED LIFE TEST BASED ON THE WEIBULL DISTRIBUTION

A MIXED CONTROL CHART ADAPTED TO THE TRUNCATED LIFE TEST BASED ON THE WEIBULL DISTRIBUTION O P E R A T I O N S R E S E A R C H A N D D E C I S I O N S No. 27 DOI:.5277/ord73 Nasrullah KHAN Muhammad ASLAM 2 Kyung-Jun KIM 3 Chi-Hyuck JUN 4 A MIXED CONTROL CHART ADAPTED TO THE TRUNCATED LIFE TEST

More information

On-Line Hardware Implementation for Complex Exponential and Logarithm

On-Line Hardware Implementation for Complex Exponential and Logarithm On-Line Hardware Implementation for Complex Exponential and Logarithm Ali SKAF, Jean-Michel MULLER * and Alain GUYOT Laboratoire TIMA / INPG - 46, Av. Félix Viallet, 3831 Grenoble Cedex * Laboratoire LIP

More information

Understanding and Using Availability

Understanding and Using Availability Understanding and Using Availability Jorge Luis Romeu, Ph.D. ASQ CQE/CRE, & Senior Member C. Stat Fellow, Royal Statistical Society Past Director, Region II (NY & PA) Director: Juarez Lincoln Marti Int

More information

A Microcontroller Implementation of Fractional Order Controller

A Microcontroller Implementation of Fractional Order Controller A Microcontroller Imlementation of Fractional Order Controller Aymen Rhouma and Hafsi Sami Université de Tunis El Manar, Ecole Nationale d Ingénieurs de Tunis, LRES Laboratoire Analyse, Concetion et Commande

More information

Fault Tolerant Quantum Computing Robert Rogers, Thomas Sylwester, Abe Pauls

Fault Tolerant Quantum Computing Robert Rogers, Thomas Sylwester, Abe Pauls CIS 410/510, Introduction to Quantum Information Theory Due: June 8th, 2016 Sring 2016, University of Oregon Date: June 7, 2016 Fault Tolerant Quantum Comuting Robert Rogers, Thomas Sylwester, Abe Pauls

More information

Research of PMU Optimal Placement in Power Systems

Research of PMU Optimal Placement in Power Systems Proceedings of the 5th WSEAS/IASME Int. Conf. on SYSTEMS THEORY and SCIENTIFIC COMPUTATION, Malta, Setember 15-17, 2005 (38-43) Research of PMU Otimal Placement in Power Systems TIAN-TIAN CAI, QIAN AI

More information

On Line Parameter Estimation of Electric Systems using the Bacterial Foraging Algorithm

On Line Parameter Estimation of Electric Systems using the Bacterial Foraging Algorithm On Line Parameter Estimation of Electric Systems using the Bacterial Foraging Algorithm Gabriel Noriega, José Restreo, Víctor Guzmán, Maribel Giménez and José Aller Universidad Simón Bolívar Valle de Sartenejas,

More information

Correspondence Between Fractal-Wavelet. Transforms and Iterated Function Systems. With Grey Level Maps. F. Mendivil and E.R.

Correspondence Between Fractal-Wavelet. Transforms and Iterated Function Systems. With Grey Level Maps. F. Mendivil and E.R. 1 Corresondence Between Fractal-Wavelet Transforms and Iterated Function Systems With Grey Level Mas F. Mendivil and E.R. Vrscay Deartment of Alied Mathematics Faculty of Mathematics University of Waterloo

More information

Monopolist s mark-up and the elasticity of substitution

Monopolist s mark-up and the elasticity of substitution Croatian Oerational Research Review 377 CRORR 8(7), 377 39 Monoolist s mark-u and the elasticity of substitution Ilko Vrankić, Mira Kran, and Tomislav Herceg Deartment of Economic Theory, Faculty of Economics

More information

A SIMPLE AD EFFICIET PARALLEL FFT ALGORITHM USIG THE BSP MODEL MARCIA A. IDA AD ROB H. BISSELIG Abstract. In this aer, we resent a new arallel radix-4

A SIMPLE AD EFFICIET PARALLEL FFT ALGORITHM USIG THE BSP MODEL MARCIA A. IDA AD ROB H. BISSELIG Abstract. In this aer, we resent a new arallel radix-4 Universiteit-Utrecht * Deartment of Mathematics A simle and ecient arallel FFT algorithm using the BSP model by Marcia A. Inda and Rob H. Bisseling Prerint nr. 3 March 2000 A SIMPLE AD EFFICIET PARALLEL

More information

Understanding and Using Availability

Understanding and Using Availability Understanding and Using Availability Jorge Luis Romeu, Ph.D. ASQ CQE/CRE, & Senior Member Email: romeu@cortland.edu htt://myrofile.cos.com/romeu ASQ/RD Webinar Series Noviembre 5, J. L. Romeu - Consultant

More information

Linear diophantine equations for discrete tomography

Linear diophantine equations for discrete tomography Journal of X-Ray Science and Technology 10 001 59 66 59 IOS Press Linear diohantine euations for discrete tomograhy Yangbo Ye a,gewang b and Jiehua Zhu a a Deartment of Mathematics, The University of Iowa,

More information

Bound on Run of Zeros and Ones for Images of Floating-Point Numbers by Algebraic Functions

Bound on Run of Zeros and Ones for Images of Floating-Point Numbers by Algebraic Functions Bound on Run of Zeros and Ones for Images of Floating-Point Numbers by Algebraic Functions Tomas Lang, Jean-Michel Muller To cite this version: Tomas Lang, Jean-Michel Muller Bound on Run of Zeros and

More information

Shadow Computing: An Energy-Aware Fault Tolerant Computing Model

Shadow Computing: An Energy-Aware Fault Tolerant Computing Model Shadow Comuting: An Energy-Aware Fault Tolerant Comuting Model Bryan Mills, Taieb Znati, Rami Melhem Deartment of Comuter Science University of Pittsburgh (bmills, znati, melhem)@cs.itt.edu Index Terms

More information

A New Method of DDB Logical Structure Synthesis Using Distributed Tabu Search

A New Method of DDB Logical Structure Synthesis Using Distributed Tabu Search A New Method of DDB Logical Structure Synthesis Using Distributed Tabu Search Eduard Babkin and Margarita Karunina 2, National Research University Higher School of Economics Det of nformation Systems and

More information

CSE 311 Lecture 02: Logic, Equivalence, and Circuits. Emina Torlak and Kevin Zatloukal

CSE 311 Lecture 02: Logic, Equivalence, and Circuits. Emina Torlak and Kevin Zatloukal CSE 311 Lecture 02: Logic, Equivalence, and Circuits Emina Torlak and Kevin Zatloukal 1 Toics Proositional logic A brief review of Lecture 01. Classifying comound roositions Converse, contraositive, and

More information

Advocating Noise as an Agent for Ultra-Low Energy Computing: Probabilistic Complementary Metal Oxide Semiconductor Devices and Their Characteristics

Advocating Noise as an Agent for Ultra-Low Energy Computing: Probabilistic Complementary Metal Oxide Semiconductor Devices and Their Characteristics Jaanese Journal of Alied Physics Vol. 45, No. 4B, 6,. 337 3316 #6 The Jaan Society of Alied Physics Advocating Noise as an Agent for Ultra-Low Energy omuting: Probabilistic omlementary Metal Oxide Semiconductor

More information

The Noise Power Ratio - Theory and ADC Testing

The Noise Power Ratio - Theory and ADC Testing The Noise Power Ratio - Theory and ADC Testing FH Irons, KJ Riley, and DM Hummels Abstract This aer develos theory behind the noise ower ratio (NPR) testing of ADCs. A mid-riser formulation is used for

More information

Cryptography. Lecture 8. Arpita Patra

Cryptography. Lecture 8. Arpita Patra Crytograhy Lecture 8 Arita Patra Quick Recall and Today s Roadma >> Hash Functions- stands in between ublic and rivate key world >> Key Agreement >> Assumtions in Finite Cyclic grous - DL, CDH, DDH Grous

More information

System Reliability Estimation and Confidence Regions from Subsystem and Full System Tests

System Reliability Estimation and Confidence Regions from Subsystem and Full System Tests 009 American Control Conference Hyatt Regency Riverfront, St. Louis, MO, USA June 0-, 009 FrB4. System Reliability Estimation and Confidence Regions from Subsystem and Full System Tests James C. Sall Abstract

More information

Multivariable Generalized Predictive Scheme for Gas Turbine Control in Combined Cycle Power Plant

Multivariable Generalized Predictive Scheme for Gas Turbine Control in Combined Cycle Power Plant Multivariable Generalized Predictive Scheme for Gas urbine Control in Combined Cycle Power Plant L.X.Niu and X.J.Liu Deartment of Automation North China Electric Power University Beiing, China, 006 e-mail

More information

Indirect Rotor Field Orientation Vector Control for Induction Motor Drives in the Absence of Current Sensors

Indirect Rotor Field Orientation Vector Control for Induction Motor Drives in the Absence of Current Sensors Indirect Rotor Field Orientation Vector Control for Induction Motor Drives in the Absence of Current Sensors Z. S. WANG *, S. L. HO ** * College of Electrical Engineering, Zhejiang University, Hangzhou

More information

Parallelism and Locality in Priority Queues. A. Ranade S. Cheng E. Deprit J. Jones S. Shih. University of California. Berkeley, CA 94720

Parallelism and Locality in Priority Queues. A. Ranade S. Cheng E. Deprit J. Jones S. Shih. University of California. Berkeley, CA 94720 Parallelism and Locality in Priority Queues A. Ranade S. Cheng E. Derit J. Jones S. Shih Comuter Science Division University of California Berkeley, CA 94720 Abstract We exlore two ways of incororating

More information

COMPARISON OF VARIOUS OPTIMIZATION TECHNIQUES FOR DESIGN FIR DIGITAL FILTERS

COMPARISON OF VARIOUS OPTIMIZATION TECHNIQUES FOR DESIGN FIR DIGITAL FILTERS NCCI 1 -National Conference on Comutational Instrumentation CSIO Chandigarh, INDIA, 19- March 1 COMPARISON OF VARIOUS OPIMIZAION ECHNIQUES FOR DESIGN FIR DIGIAL FILERS Amanjeet Panghal 1, Nitin Mittal,Devender

More information

A PROBABILISTIC POWER ESTIMATION METHOD FOR COMBINATIONAL CIRCUITS UNDER REAL GATE DELAY MODEL

A PROBABILISTIC POWER ESTIMATION METHOD FOR COMBINATIONAL CIRCUITS UNDER REAL GATE DELAY MODEL A PROBABILISTIC POWER ESTIMATION METHOD FOR COMBINATIONAL CIRCUITS UNDER REAL GATE DELAY MODEL G. Theodoridis, S. Theoharis, D. Soudris*, C. Goutis VLSI Design Lab, Det. of Electrical and Comuter Eng.

More information

ANALYTICAL MODEL FOR DYNAMIC AVALANCHE. Universitat der Bundeswehr Munchen, Germany. *Siemens AG, Corporate Technology, Munich, Germany

ANALYTICAL MODEL FOR DYNAMIC AVALANCHE. Universitat der Bundeswehr Munchen, Germany. *Siemens AG, Corporate Technology, Munich, Germany ANALYTICAL MODEL FOR DYNAMIC AVALANCHE BREAKDOWN IN POWER DEVICES L. Gohler J. Sigg* Universitat der Bundeswehr Munchen Germany *Siemens AG Cororate Technology Munich Germany Abstract. The behaviour of

More information

A Simple Weight Decay Can Improve. Abstract. It has been observed in numerical simulations that a weight decay can improve

A Simple Weight Decay Can Improve. Abstract. It has been observed in numerical simulations that a weight decay can improve In Advances in Neural Information Processing Systems 4, J.E. Moody, S.J. Hanson and R.P. Limann, eds. Morgan Kaumann Publishers, San Mateo CA, 1995,. 950{957. A Simle Weight Decay Can Imrove Generalization

More information

An Introduction To Range Searching

An Introduction To Range Searching An Introduction To Range Searching Jan Vahrenhold eartment of Comuter Science Westfälische Wilhelms-Universität Münster, Germany. Overview 1. Introduction: Problem Statement, Lower Bounds 2. Range Searching

More information

Recent Developments in Multilayer Perceptron Neural Networks

Recent Developments in Multilayer Perceptron Neural Networks Recent Develoments in Multilayer Percetron eural etworks Walter H. Delashmit Lockheed Martin Missiles and Fire Control Dallas, Texas 75265 walter.delashmit@lmco.com walter.delashmit@verizon.net Michael

More information

Optimal Design of Truss Structures Using a Neutrosophic Number Optimization Model under an Indeterminate Environment

Optimal Design of Truss Structures Using a Neutrosophic Number Optimization Model under an Indeterminate Environment Neutrosohic Sets and Systems Vol 14 016 93 University of New Mexico Otimal Design of Truss Structures Using a Neutrosohic Number Otimization Model under an Indeterminate Environment Wenzhong Jiang & Jun

More information

Design Constraint for Fine Grain Supply Voltage Control LSI

Design Constraint for Fine Grain Supply Voltage Control LSI ASP-DAC 211 Designer s Forum Session 8D-3: State-of-The-Art SoCs and Design Methodologies Design Constraint for Fine Grain Suly Voltage Control LSI January 28, 211 Atsuki Inoue Platform Technologies Laboratories

More information

NUMERICAL AND THEORETICAL INVESTIGATIONS ON DETONATION- INERT CONFINEMENT INTERACTIONS

NUMERICAL AND THEORETICAL INVESTIGATIONS ON DETONATION- INERT CONFINEMENT INTERACTIONS NUMERICAL AND THEORETICAL INVESTIGATIONS ON DETONATION- INERT CONFINEMENT INTERACTIONS Tariq D. Aslam and John B. Bdzil Los Alamos National Laboratory Los Alamos, NM 87545 hone: 1-55-667-1367, fax: 1-55-667-6372

More information

Genetic Algorithms, Selection Schemes, and the Varying Eects of Noise. IlliGAL Report No November Department of General Engineering

Genetic Algorithms, Selection Schemes, and the Varying Eects of Noise. IlliGAL Report No November Department of General Engineering Genetic Algorithms, Selection Schemes, and the Varying Eects of Noise Brad L. Miller Det. of Comuter Science University of Illinois at Urbana-Chamaign David E. Goldberg Det. of General Engineering University

More information

Analysis of some entrance probabilities for killed birth-death processes

Analysis of some entrance probabilities for killed birth-death processes Analysis of some entrance robabilities for killed birth-death rocesses Master s Thesis O.J.G. van der Velde Suervisor: Dr. F.M. Sieksma July 5, 207 Mathematical Institute, Leiden University Contents Introduction

More information

START Selected Topics in Assurance

START Selected Topics in Assurance START Selected Toics in Assurance Related Technologies Table of Contents Introduction Statistical Models for Simle Systems (U/Down) and Interretation Markov Models for Simle Systems (U/Down) and Interretation

More information

An Analysis of Reliable Classifiers through ROC Isometrics

An Analysis of Reliable Classifiers through ROC Isometrics An Analysis of Reliable Classifiers through ROC Isometrics Stijn Vanderlooy s.vanderlooy@cs.unimaas.nl Ida G. Srinkhuizen-Kuyer kuyer@cs.unimaas.nl Evgueni N. Smirnov smirnov@cs.unimaas.nl MICC-IKAT, Universiteit

More information

ON LINEAR COMPLEXITY OF GENERALIZED SHRINKING-MULTIPLEXING GENERATOR

ON LINEAR COMPLEXITY OF GENERALIZED SHRINKING-MULTIPLEXING GENERATOR Journal of Basic and Alied Research International 4(1): 8 17, 015 O LIEAR COMPLEXITY OF GEERALIZED SHRIKIG-MULTIPLEXIG GEERATOR ZHAETA. TASHEVA 1* 1 Faculty of Artillery, AAD and CIS, ational Military

More information

Keywords: Vocal Tract; Lattice model; Reflection coefficients; Linear Prediction; Levinson algorithm.

Keywords: Vocal Tract; Lattice model; Reflection coefficients; Linear Prediction; Levinson algorithm. Volume 3, Issue 6, June 213 ISSN: 2277 128X International Journal of Advanced Research in Comuter Science and Software Engineering Research Paer Available online at: www.ijarcsse.com Lattice Filter Model

More information

Modeling and Estimation of Full-Chip Leakage Current Considering Within-Die Correlation

Modeling and Estimation of Full-Chip Leakage Current Considering Within-Die Correlation 6.3 Modeling and Estimation of Full-Chi Leaage Current Considering Within-Die Correlation Khaled R. eloue, Navid Azizi, Farid N. Najm Deartment of ECE, University of Toronto,Toronto, Ontario, Canada {haled,nazizi,najm}@eecg.utoronto.ca

More information

CSC165H, Mathematical expression and reasoning for computer science week 12

CSC165H, Mathematical expression and reasoning for computer science week 12 CSC165H, Mathematical exression and reasoning for comuter science week 1 nd December 005 Gary Baumgartner and Danny Hea hea@cs.toronto.edu SF4306A 416-978-5899 htt//www.cs.toronto.edu/~hea/165/s005/index.shtml

More information

arxiv: v2 [quant-ph] 2 Aug 2012

arxiv: v2 [quant-ph] 2 Aug 2012 Qcomiler: quantum comilation with CSD method Y. G. Chen a, J. B. Wang a, a School of Physics, The University of Western Australia, Crawley WA 6009 arxiv:208.094v2 [quant-h] 2 Aug 202 Abstract In this aer,

More information

Yang Y * and Jung I U.S. NRC Abstract

Yang Y * and Jung I U.S. NRC  Abstract International Journal of afety cience Vol. 01, No. 01, 2017,. 12-19 OI:10.24900/01011219.2017.0301 oolean lgebra lication in imlifying ault Tree nalysis Yang Y * and Jung I U.. NR yaguang.yang@nrc.gov,

More information

Chapter 9 Practical cycles

Chapter 9 Practical cycles Prof.. undararajan Chater 9 Practical cycles 9. Introduction In Chaters 7 and 8, it was shown that a reversible engine based on the Carnot cycle (two reversible isothermal heat transfers and two reversible

More information

Analyses of Orthogonal and Non-Orthogonal Steering Vectors at Millimeter Wave Systems

Analyses of Orthogonal and Non-Orthogonal Steering Vectors at Millimeter Wave Systems Analyses of Orthogonal and Non-Orthogonal Steering Vectors at Millimeter Wave Systems Hsiao-Lan Chiang, Tobias Kadur, and Gerhard Fettweis Vodafone Chair for Mobile Communications Technische Universität

More information

Estimation of component redundancy in optimal age maintenance

Estimation of component redundancy in optimal age maintenance EURO MAINTENANCE 2012, Belgrade 14-16 May 2012 Proceedings of the 21 st International Congress on Maintenance and Asset Management Estimation of comonent redundancy in otimal age maintenance Jorge ioa

More information

8 STOCHASTIC PROCESSES

8 STOCHASTIC PROCESSES 8 STOCHASTIC PROCESSES The word stochastic is derived from the Greek στoχαστικoς, meaning to aim at a target. Stochastic rocesses involve state which changes in a random way. A Markov rocess is a articular

More information

How to Estimate Expected Shortfall When Probabilities Are Known with Interval or Fuzzy Uncertainty

How to Estimate Expected Shortfall When Probabilities Are Known with Interval or Fuzzy Uncertainty How to Estimate Exected Shortfall When Probabilities Are Known with Interval or Fuzzy Uncertainty Christian Servin Information Technology Deartment El Paso Community College El Paso, TX 7995, USA cservin@gmail.com

More information

Laboratoire de l Informatique du Parallélisme

Laboratoire de l Informatique du Parallélisme Laboratoire de l Informatique du Parallélisme Ecole Normale Supérieure de Lyon Unité de recherche associée au CNRS n 1398 Reciprocation, Square root, Inverse Square Root, and some Elementary Functions

More information

Tests for Two Proportions in a Stratified Design (Cochran/Mantel-Haenszel Test)

Tests for Two Proportions in a Stratified Design (Cochran/Mantel-Haenszel Test) Chater 225 Tests for Two Proortions in a Stratified Design (Cochran/Mantel-Haenszel Test) Introduction In a stratified design, the subects are selected from two or more strata which are formed from imortant

More information

Matching Partition a Linked List and Its Optimization

Matching Partition a Linked List and Its Optimization Matching Partition a Linked List and Its Otimization Yijie Han Deartment of Comuter Science University of Kentucky Lexington, KY 40506 ABSTRACT We show the curve O( n log i + log (i) n + log i) for the

More information

arxiv: v1 [physics.data-an] 26 Oct 2012

arxiv: v1 [physics.data-an] 26 Oct 2012 Constraints on Yield Parameters in Extended Maximum Likelihood Fits Till Moritz Karbach a, Maximilian Schlu b a TU Dortmund, Germany, moritz.karbach@cern.ch b TU Dortmund, Germany, maximilian.schlu@cern.ch

More information

An Investigation on the Numerical Ill-conditioning of Hybrid State Estimators

An Investigation on the Numerical Ill-conditioning of Hybrid State Estimators An Investigation on the Numerical Ill-conditioning of Hybrid State Estimators S. K. Mallik, Student Member, IEEE, S. Chakrabarti, Senior Member, IEEE, S. N. Singh, Senior Member, IEEE Deartment of Electrical

More information

1. Introduction. 2. Background of elliptic curve group. Identity-based Digital Signature Scheme Without Bilinear Pairings

1. Introduction. 2. Background of elliptic curve group. Identity-based Digital Signature Scheme Without Bilinear Pairings Identity-based Digital Signature Scheme Without Bilinear Pairings He Debiao, Chen Jianhua, Hu Jin School of Mathematics Statistics, Wuhan niversity, Wuhan, Hubei, China, 43007 Abstract: Many identity-based

More information

ute measures of uncertainty called standard errors for these b j estimates and the resulting forecasts if certain conditions are satis- ed. Note the e

ute measures of uncertainty called standard errors for these b j estimates and the resulting forecasts if certain conditions are satis- ed. Note the e Regression with Time Series Errors David A. Dickey, North Carolina State University Abstract: The basic assumtions of regression are reviewed. Grahical and statistical methods for checking the assumtions

More information

The Recursive Fitting of Multivariate. Complex Subset ARX Models

The Recursive Fitting of Multivariate. Complex Subset ARX Models lied Mathematical Sciences, Vol. 1, 2007, no. 23, 1129-1143 The Recursive Fitting of Multivariate Comlex Subset RX Models Jack Penm School of Finance and lied Statistics NU College of Business & conomics

More information

Cryptanalysis of Pseudorandom Generators

Cryptanalysis of Pseudorandom Generators CSE 206A: Lattice Algorithms and Alications Fall 2017 Crytanalysis of Pseudorandom Generators Instructor: Daniele Micciancio UCSD CSE As a motivating alication for the study of lattice in crytograhy we

More information

Uncertainty Modeling with Interval Type-2 Fuzzy Logic Systems in Mobile Robotics

Uncertainty Modeling with Interval Type-2 Fuzzy Logic Systems in Mobile Robotics Uncertainty Modeling with Interval Tye-2 Fuzzy Logic Systems in Mobile Robotics Ondrej Linda, Student Member, IEEE, Milos Manic, Senior Member, IEEE bstract Interval Tye-2 Fuzzy Logic Systems (IT2 FLSs)

More information

Lilian Markenzon 1, Nair Maria Maia de Abreu 2* and Luciana Lee 3

Lilian Markenzon 1, Nair Maria Maia de Abreu 2* and Luciana Lee 3 Pesquisa Oeracional (2013) 33(1): 123-132 2013 Brazilian Oerations Research Society Printed version ISSN 0101-7438 / Online version ISSN 1678-5142 www.scielo.br/oe SOME RESULTS ABOUT THE CONNECTIVITY OF

More information

Heuristics on Tate Shafarevitch Groups of Elliptic Curves Defined over Q

Heuristics on Tate Shafarevitch Groups of Elliptic Curves Defined over Q Heuristics on Tate Shafarevitch Grous of Ellitic Curves Defined over Q Christohe Delaunay CONTENTS. Introduction 2. Dirichlet Series and Averages 3. Heuristics on Tate Shafarevitch Grous References In

More information

Approximating min-max k-clustering

Approximating min-max k-clustering Aroximating min-max k-clustering Asaf Levin July 24, 2007 Abstract We consider the roblems of set artitioning into k clusters with minimum total cost and minimum of the maximum cost of a cluster. The cost

More information

1-way quantum finite automata: strengths, weaknesses and generalizations

1-way quantum finite automata: strengths, weaknesses and generalizations 1-way quantum finite automata: strengths, weaknesses and generalizations arxiv:quant-h/9802062v3 30 Se 1998 Andris Ambainis UC Berkeley Abstract Rūsiņš Freivalds University of Latvia We study 1-way quantum

More information

Neural network models for river flow forecasting

Neural network models for river flow forecasting Neural network models for river flow forecasting Nguyen Tan Danh Huynh Ngoc Phien* and Ashim Das Guta Asian Institute of Technology PO Box 4 KlongLuang 220 Pathumthani Thailand Abstract In this study back

More information

Theory of Parallel Hardware May 11, 2004 Massachusetts Institute of Technology Charles Leiserson, Michael Bender, Bradley Kuszmaul

Theory of Parallel Hardware May 11, 2004 Massachusetts Institute of Technology Charles Leiserson, Michael Bender, Bradley Kuszmaul Theory of Parallel Hardware May 11, 2004 Massachusetts Institute of Technology 6.896 Charles Leiserson, Michael Bender, Bradley Kuszmaul Final Examination Final Examination ffl Do not oen this exam booklet

More information

J. Electrical Systems 13-2 (2017): Regular paper

J. Electrical Systems 13-2 (2017): Regular paper Menxi Xie,*, CanYan Zhu, BingWei Shi 2, Yong Yang 2 J. Electrical Systems 3-2 (207): 332-347 Regular aer Power Based Phase-Locked Loo Under Adverse Conditions with Moving Average Filter for Single-Phase

More information

Mathematical Efficiency Modeling of Static Power Converters

Mathematical Efficiency Modeling of Static Power Converters Fabrício Hoff Duont Regional Integrated University of Uer Uruguai and Missions (URI Av. Assis Brasil, 9, 980 000 Frederico Westhalen, RS, Brazil Contact: fhd@ieee.org Mathematical Efficiency Modeling of

More information

State Estimation with ARMarkov Models

State Estimation with ARMarkov Models Deartment of Mechanical and Aerosace Engineering Technical Reort No. 3046, October 1998. Princeton University, Princeton, NJ. State Estimation with ARMarkov Models Ryoung K. Lim 1 Columbia University,

More information

Uncorrelated Multilinear Principal Component Analysis for Unsupervised Multilinear Subspace Learning

Uncorrelated Multilinear Principal Component Analysis for Unsupervised Multilinear Subspace Learning TNN-2009-P-1186.R2 1 Uncorrelated Multilinear Princial Comonent Analysis for Unsuervised Multilinear Subsace Learning Haiing Lu, K. N. Plataniotis and A. N. Venetsanooulos The Edward S. Rogers Sr. Deartment

More information

Synthesis of Moore FSM with Expanded Coding Space

Synthesis of Moore FSM with Expanded Coding Space Volume 3 Issue, January 24 Synthesis of oore FS with Exanded Coding Sace Olena Hebda, Larysa Titarenko Institute of Comuter Engineering and Electronics University of Zielona Góra Zielona Góra, Poland Email:

More information

Multilayer Perceptron Neural Network (MLPs) For Analyzing the Properties of Jordan Oil Shale

Multilayer Perceptron Neural Network (MLPs) For Analyzing the Properties of Jordan Oil Shale World Alied Sciences Journal 5 (5): 546-552, 2008 ISSN 1818-4952 IDOSI Publications, 2008 Multilayer Percetron Neural Network (MLPs) For Analyzing the Proerties of Jordan Oil Shale 1 Jamal M. Nazzal, 2

More information

x and y suer from two tyes of additive noise [], [3] Uncertainties e x, e y, where the only rior knowledge is their boundedness and zero mean Gaussian

x and y suer from two tyes of additive noise [], [3] Uncertainties e x, e y, where the only rior knowledge is their boundedness and zero mean Gaussian A New Estimator for Mixed Stochastic and Set Theoretic Uncertainty Models Alied to Mobile Robot Localization Uwe D. Hanebeck Joachim Horn Institute of Automatic Control Engineering Siemens AG, Cororate

More information