Pop-Click Noise Detection Using Inter-Frame Correlation for Improved Portable Auditory Sensing

Size: px
Start display at page:

Download "Pop-Click Noise Detection Using Inter-Frame Correlation for Improved Portable Auditory Sensing"

Transcription

1 Advanced Scence and Technology Letters, pp Pop-Clc Nose Detecton Usng Inter-Frame Correlaton for Improved Portable Audtory Sensng Dong Yun Lee, Kwang Myung Jeon, and Hong Koo Km School of Informaton and Communcatons Gwangju Insttute of Scence and Technology (GIST) {ldy, mjeon, Abstract. In ths paper, a pop-clc nose detecton method s proposed to mprove the qualty of audo sgnals recorded usng portable mcrophones. In order to reduce false alarm and mssng detecton errors, the proposed method utlzes the second-order dfference of an uncorrelated resdual sgnal, followed by adaptve medan thresholdng. It s shown from performance evaluaton that the proposed method acheves hgher detecton accuracy, under varous sgnal-tonose rato condtons, than wth a conventonal method usng the frst-order dfference of the resdual sgnal. Keywords: Pop-clc nose, lnear predcton, dfference of resdual sgnal, adaptve medan thresholdng 1 Introducton When an audo sgnal s recorded by portable audtory sensors such as a condenser mcrophone or a mcro electrcal-mechancal system (MEMS) mcrophone, there are many factors that generate nose. In partcular, a pop-clc nose s generated by varous physcal phenomena n acoustcs, such as touchng screens, clcng buttons, and so on [1]. Interference by such noses whle recordng can be hghly annoyng to most lsteners. In order to detect a pop-clc nose, there have been many nose detecton methods proposed [1 4]. Among them, the technques usng the resdual sgnal [3] and the frst-order dfference of the resdual sgnal [4] were reported to successfully detect pop-clc noses. However, the error rate ncreased extremely n the nterval where the sgnal-to-nose rato (SNR) was hgh [4]. Thus, n order to mprove detecton accuracy under hgh SNR condtons, the proposed pop-clc nose detecton method frst utlzes the second-order dfference of an uncorrelated resdual sgnal. Ths gves more emphass on a pop-clc nose as t has strong energy n the hgh frequency band. Next, adaptve medan threshold [5][6] s appled at those values to determne whether or not there s a pop-clc nose. Followng ths ntroducton, Secton 2 proposes a pop-clc nose detecton method usng the second-order dfference of an uncorrelated resdual sgnal. Next, Secton 3 evaluates the performance of the proposed method and compares t wth that of a ISSN: ASTL Copyrght 2013 SERSC

2 Advanced Scence and Technology Letters Fg. 1. Procedure of the proposed pop-clc nose detecton method. conventonal method usng the frst-order dfference of the resdual sgnal. Fnally, Secton 4 concludes the paper. 2 Proposed Pop-Clc Nose Detecton Method Fg. 1 shows an overall procedure of the proposed pop-clc nose detecton method. As shown n the fgure, the resdual sgnal of the -th frame, e, s frst obtaned by the lnear predcton (LP) technque, defned as where p e = s a s ( n ) (1) = 1 a and s are the -th LP coeffcent and the n-th nput sample of the -th frame, respectvely. In addton, p s the lnear predcton order. Smlarly to Eq. (1), the resdual sgnal of the nput sgnal appled to the (-1)-th lnear predcton flter, e M, s obtaned as e M p = 1 1 = s a s ( n ) (2) 1 where a s the -th LP coeffcent obtaned from the (-1)-th frame. The dfference between e and e M corresponds to an uncorrelated resdual sgnal between the -th and (-1)-th frames, whch s obtaned as e D M = e e. (3) Next, the absolute value of the second-order dfference of an uncorrelated resdual sgnal s obtaned as D D D g = e ( n 1) 2 e + e ( n + 1). (4) Copyrght 2013 SERSC 165

3 Advanced Scence and Technology Letters Table 2. Comparson of F-measure values between two pop-clc nose detecton methods at 15 db SNR. LP order Conventonal method Proposed method The g n Eq. (4) becomes large durng nose ntervals, thus t s used to decde whether or not the -th frame ncludes a pop-clc nose. The decson s actually performed by applyng adaptve medan thresholdng to g, such that 1, f g > θ med( g ( n m),, g,, g ( n + m)) N( ) = 0, otherwse (5) where med ( ), θ, and m are a medan flter, a scale factor, and the coverage of the medan flter, respectvely. In Eq. (5), N () ndcates the presence of pop-clc nose or not by ts value. In other words, a pop-clc nose s detected, that s, N ( ) = 1, f the value of the second-order dfference of an uncorrelated resdual sgnal s hgher than the value of the medan threshold. Otherwse, N ( ) = 0, whch means there s no pop-clc nose wthn the -th frame. 3 Performance Evaluaton The performance of the proposed method was evaluated by usng F-measure [7], and t was compared wth that of a conventonal method usng the frst-order dfference of the resdual sgnal. For the test, three male and three female voce sgnals, sampled at 48 Hz, were chosen. Each sample was one mnute long wth 100 pop-clc noses n total. For the analyss, each sgnal was segmented nto consecutve frames by applyng a Hannng wndow whose length was 4,096 samples, where each frame was overlapped by half wth the prevous frame. Note here that the parameters n Eq. (5) for medan threshold were set as θ = 50 and m = 30. Frst, n order to select a sutable LP order, the detecton accuracy was measure dependng on the LP order at 15 db SNR. Table 1 compares F-measure values between the conventonal and proposed methods for four dfferent LP orders. It was shown from the table that the proposed method provded hgher F-measure value than the conventonal method for all LP orders. The hghest detecton accuracy was acheved when LP order was sx. Thus, the LP order was set to sx for the next experment. Second, n order to evaluate the performance of the detecton under SNR condtons, pop-clc noses were mxed to have dfferent SNRs from 0 25 db at 5 db ncrements. The hgher SNR means that a pop-clc nose has lower power compared wth that of the orgnal sgnal. Fg. 2 also compares F-measure values between the conventonal and proposed methods under dfferent SNRs. It was shown from the fgure that the proposed method had hgher F-measure values than the conventonal method under all the SNRs. 166 Copyrght 2013 SERSC

4 Advanced Scence and Technology Letters Fg. 2. F-measure values of the conventonal and proposed methods under dfferent SNRs rangng from 0 25 db. 4 Concluson In ths paper, a pop-clc nose detecton method was proposed for mproved portable audtory sensng. The proposed method used second-order dfference of an uncorrelated resdual sgnal, and t acheved hgher pop-clc nose detecton accuracy by 4.43% than wth a conventonal method usng the frst-order dfference of the resdual sgnal. Acnowledgments. Ths wor was supported n part by the NRF grant funded by the government of Korea (MSIP) (No ), and by the MSIP, Korea, under the ITRC support program supervsed by the NIPA (NIPA-2013-H ). References 1. Sadler, B. M.: Detecton n correlated mpulsve nose usng fourth-order cumulants. IEEE Transactons on Sgnal Processng, 44(11), (1996) pp Chandra, C., Moore, M. S., Mtra, S. K.: An effcent method for the removal of mpulse nose from speech and audo sgnals. In: Proceedngs of ISCAS, (1998) pp Kauppnen, I.: Methods for detectng mpulsve nose n speech and audo sgnals. In: Proceedngs of Internatonal Conference on 14th Dgtal Sgnal Processng, (2002) pp Hong, J., Par, J., Han, S., Hahn, M.: Sporadc nose reducton for robust speech recognton n moble devces. In: Proceedngs of IEEE Internatonal Conference on Consumer Electroncs, (2011) pp Chen, T., Wu, H. R.: Adaptve mpulse detecton usng center-weghted medan flters. IEEE Sgnal Processng Letters, 8(1), (2001) pp Copyrght 2013 SERSC 167

5 Advanced Scence and Technology Letters 6. Esquef, P. A. A., Bscanho, L. W. P., Dnz, P. S. R., Freeland, F. P.: A double-thresholdbased approach to mpulsve nose detecton n audo sgnals. In: Proceedngs of EUSIPCO, (2000) pp Powers, D. M. W.: Evaluaton: from precson, recall and F-measure to ROC, nformedness, maredness & correlaton. Journal of Machne Learnng Technologes, 2(1), (2011) pp Copyrght 2013 SERSC

An Improved multiple fractal algorithm

An Improved multiple fractal algorithm Advanced Scence and Technology Letters Vol.31 (MulGraB 213), pp.184-188 http://dx.do.org/1.1427/astl.213.31.41 An Improved multple fractal algorthm Yun Ln, Xaochu Xu, Jnfeng Pang College of Informaton

More information

IMAGE DENOISING USING NEW ADAPTIVE BASED MEDIAN FILTER

IMAGE DENOISING USING NEW ADAPTIVE BASED MEDIAN FILTER Sgnal & Image Processng : An Internatonal Journal (SIPIJ) Vol.5, No.4, August 2014 IMAGE DENOISING USING NEW ADAPTIVE BASED MEDIAN FILTER Suman Shrestha 1, 2 1 Unversty of Massachusetts Medcal School,

More information

Multigradient for Neural Networks for Equalizers 1

Multigradient for Neural Networks for Equalizers 1 Multgradent for Neural Netorks for Equalzers 1 Chulhee ee, Jnook Go and Heeyoung Km Department of Electrcal and Electronc Engneerng Yonse Unversty 134 Shnchon-Dong, Seodaemun-Ku, Seoul 1-749, Korea ABSTRACT

More information

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur Module 3 LOSSY IMAGE COMPRESSION SYSTEMS Verson ECE IIT, Kharagpur Lesson 6 Theory of Quantzaton Verson ECE IIT, Kharagpur Instructonal Objectves At the end of ths lesson, the students should be able to:

More information

A Novel Fuzzy logic Based Impulse Noise Filtering Technique

A Novel Fuzzy logic Based Impulse Noise Filtering Technique Internatonal Journal of Advanced Scence and Technology A Novel Fuzzy logc Based Impulse Nose Flterng Technque Aborsade, D.O Department of Electroncs Engneerng, Ladoke Akntola Unversty of Tech., Ogbomoso.

More information

CHAPTER 4 SPEECH ENHANCEMENT USING MULTI-BAND WIENER FILTER. In real environmental conditions the speech signal may be

CHAPTER 4 SPEECH ENHANCEMENT USING MULTI-BAND WIENER FILTER. In real environmental conditions the speech signal may be 55 CHAPTER 4 SPEECH ENHANCEMENT USING MULTI-BAND WIENER FILTER 4.1 Introducton In real envronmental condtons the speech sgnal may be supermposed by the envronmental nterference. In general, the spectrum

More information

CONTRAST ENHANCEMENT FOR MIMIMUM MEAN BRIGHTNESS ERROR FROM HISTOGRAM PARTITIONING INTRODUCTION

CONTRAST ENHANCEMENT FOR MIMIMUM MEAN BRIGHTNESS ERROR FROM HISTOGRAM PARTITIONING INTRODUCTION CONTRAST ENHANCEMENT FOR MIMIMUM MEAN BRIGHTNESS ERROR FROM HISTOGRAM PARTITIONING N. Phanthuna 1,2, F. Cheevasuvt 2 and S. Chtwong 2 1 Department of Electrcal Engneerng, Faculty of Engneerng Rajamangala

More information

STUDY OF A THREE-AXIS PIEZORESISTIVE ACCELEROMETER WITH UNIFORM AXIAL SENSITIVITIES

STUDY OF A THREE-AXIS PIEZORESISTIVE ACCELEROMETER WITH UNIFORM AXIAL SENSITIVITIES STUDY OF A THREE-AXIS PIEZORESISTIVE ACCELEROMETER WITH UNIFORM AXIAL SENSITIVITIES Abdelkader Benchou, PhD Canddate Nasreddne Benmoussa, PhD Kherreddne Ghaffour, PhD Unversty of Tlemcen/Unt of Materals

More information

Chapter 13: Multiple Regression

Chapter 13: Multiple Regression Chapter 13: Multple Regresson 13.1 Developng the multple-regresson Model The general model can be descrbed as: It smplfes for two ndependent varables: The sample ft parameter b 0, b 1, and b are used to

More information

Parameter Estimation for Dynamic System using Unscented Kalman filter

Parameter Estimation for Dynamic System using Unscented Kalman filter Parameter Estmaton for Dynamc System usng Unscented Kalman flter Jhoon Seung 1,a, Amr Atya F. 2,b, Alexander G.Parlos 3,c, and Klto Chong 1,4,d* 1 Dvson of Electroncs Engneerng, Chonbuk Natonal Unversty,

More information

Average Decision Threshold of CA CFAR and excision CFAR Detectors in the Presence of Strong Pulse Jamming 1

Average Decision Threshold of CA CFAR and excision CFAR Detectors in the Presence of Strong Pulse Jamming 1 Average Decson hreshold of CA CFAR and excson CFAR Detectors n the Presence of Strong Pulse Jammng Ivan G. Garvanov and Chrsto A. Kabachev Insttute of Informaton echnologes Bulgaran Academy of Scences

More information

The Study of Teaching-learning-based Optimization Algorithm

The Study of Teaching-learning-based Optimization Algorithm Advanced Scence and Technology Letters Vol. (AST 06), pp.05- http://dx.do.org/0.57/astl.06. The Study of Teachng-learnng-based Optmzaton Algorthm u Sun, Yan fu, Lele Kong, Haolang Q,, Helongang Insttute

More information

Department of Electrical & Electronic Engineeing Imperial College London. E4.20 Digital IC Design. Median Filter Project Specification

Department of Electrical & Electronic Engineeing Imperial College London. E4.20 Digital IC Design. Median Filter Project Specification Desgn Project Specfcaton Medan Flter Department of Electrcal & Electronc Engneeng Imperal College London E4.20 Dgtal IC Desgn Medan Flter Project Specfcaton A medan flter s used to remove nose from a sampled

More information

Inductance Calculation for Conductors of Arbitrary Shape

Inductance Calculation for Conductors of Arbitrary Shape CRYO/02/028 Aprl 5, 2002 Inductance Calculaton for Conductors of Arbtrary Shape L. Bottura Dstrbuton: Internal Summary In ths note we descrbe a method for the numercal calculaton of nductances among conductors

More information

Low Complexity Soft-Input Soft-Output Hamming Decoder

Low Complexity Soft-Input Soft-Output Hamming Decoder Low Complexty Soft-Input Soft-Output Hammng Der Benjamn Müller, Martn Holters, Udo Zölzer Helmut Schmdt Unversty Unversty of the Federal Armed Forces Department of Sgnal Processng and Communcatons Holstenhofweg

More information

Microwave Diversity Imaging Compression Using Bioinspired

Microwave Diversity Imaging Compression Using Bioinspired Mcrowave Dversty Imagng Compresson Usng Bonspred Neural Networks Youwe Yuan 1, Yong L 1, Wele Xu 1, Janghong Yu * 1 School of Computer Scence and Technology, Hangzhou Danz Unversty, Hangzhou, Zhejang,

More information

Multiple Sound Source Location in 3D Space with a Synchronized Neural System

Multiple Sound Source Location in 3D Space with a Synchronized Neural System Multple Sound Source Locaton n D Space wth a Synchronzed Neural System Yum Takzawa and Atsush Fukasawa Insttute of Statstcal Mathematcs Research Organzaton of Informaton and Systems 0- Mdor-cho, Tachkawa,

More information

Turbulence classification of load data by the frequency and severity of wind gusts. Oscar Moñux, DEWI GmbH Kevin Bleibler, DEWI GmbH

Turbulence classification of load data by the frequency and severity of wind gusts. Oscar Moñux, DEWI GmbH Kevin Bleibler, DEWI GmbH Turbulence classfcaton of load data by the frequency and severty of wnd gusts Introducton Oscar Moñux, DEWI GmbH Kevn Blebler, DEWI GmbH Durng the wnd turbne developng process, one of the most mportant

More information

Copyright 2017 by Taylor Enterprises, Inc., All Rights Reserved. Adjusted Control Limits for P Charts. Dr. Wayne A. Taylor

Copyright 2017 by Taylor Enterprises, Inc., All Rights Reserved. Adjusted Control Limits for P Charts. Dr. Wayne A. Taylor Taylor Enterprses, Inc. Control Lmts for P Charts Copyrght 2017 by Taylor Enterprses, Inc., All Rghts Reserved. Control Lmts for P Charts Dr. Wayne A. Taylor Abstract: P charts are used for count data

More information

is the calculated value of the dependent variable at point i. The best parameters have values that minimize the squares of the errors

is the calculated value of the dependent variable at point i. The best parameters have values that minimize the squares of the errors Multple Lnear and Polynomal Regresson wth Statstcal Analyss Gven a set of data of measured (or observed) values of a dependent varable: y versus n ndependent varables x 1, x, x n, multple lnear regresson

More information

Impulse Noise Removal Technique Based on Fuzzy Logic

Impulse Noise Removal Technique Based on Fuzzy Logic Impulse Nose Removal Technque Based on Fuzzy Logc 1 Mthlesh Atulkar, 2 A.S. Zadgaonkar and 3 Sanjay Kumar C V Raman Unversty, Kota, Blaspur, Inda 1 m.atulkar@gmal.com, 2 arunzad28@hotmal.com, 3 sanrapur@redffmal.com

More information

Negative Binomial Regression

Negative Binomial Regression STATGRAPHICS Rev. 9/16/2013 Negatve Bnomal Regresson Summary... 1 Data Input... 3 Statstcal Model... 3 Analyss Summary... 4 Analyss Optons... 7 Plot of Ftted Model... 8 Observed Versus Predcted... 10 Predctons...

More information

Improvement of Histogram Equalization for Minimum Mean Brightness Error

Improvement of Histogram Equalization for Minimum Mean Brightness Error Proceedngs of the 7 WSEAS Int. Conference on Crcuts, Systems, Sgnal and elecommuncatons, Gold Coast, Australa, January 7-9, 7 3 Improvement of Hstogram Equalzaton for Mnmum Mean Brghtness Error AAPOG PHAHUA*,

More information

Orientation Model of Elite Education and Mass Education

Orientation Model of Elite Education and Mass Education Proceedngs of the 8th Internatonal Conference on Innovaton & Management 723 Orentaton Model of Elte Educaton and Mass Educaton Ye Peng Huanggang Normal Unversty, Huanggang, P.R.Chna, 438 (E-mal: yepeng@hgnc.edu.cn)

More information

FFT Based Spectrum Analysis of Three Phase Signals in Park (d-q) Plane

FFT Based Spectrum Analysis of Three Phase Signals in Park (d-q) Plane Proceedngs of the 00 Internatonal Conference on Industral Engneerng and Operatons Management Dhaka, Bangladesh, January 9 0, 00 FFT Based Spectrum Analyss of Three Phase Sgnals n Park (d-q) Plane Anuradha

More information

A New Scrambling Evaluation Scheme based on Spatial Distribution Entropy and Centroid Difference of Bit-plane

A New Scrambling Evaluation Scheme based on Spatial Distribution Entropy and Centroid Difference of Bit-plane A New Scramblng Evaluaton Scheme based on Spatal Dstrbuton Entropy and Centrod Dfference of Bt-plane Lang Zhao *, Avshek Adhkar Kouch Sakura * * Graduate School of Informaton Scence and Electrcal Engneerng,

More information

Regularized Discriminant Analysis for Face Recognition

Regularized Discriminant Analysis for Face Recognition 1 Regularzed Dscrmnant Analyss for Face Recognton Itz Pma, Mayer Aladem Department of Electrcal and Computer Engneerng, Ben-Guron Unversty of the Negev P.O.Box 653, Beer-Sheva, 845, Israel. Abstract Ths

More information

White Noise Reduction of Audio Signal using Wavelets Transform with Modified Universal Threshold

White Noise Reduction of Audio Signal using Wavelets Transform with Modified Universal Threshold Whte Nose Reducton of Audo Sgnal usng Wavelets Transform wth Modfed Unversal Threshold MATKO SARIC, LUKI BILICIC, HRVOJE DUJMIC Unversty of Splt R.Boskovca b.b, HR 1000 Splt CROATIA Abstract: - Ths paper

More information

COMPUTATIONALLY EFFICIENT WAVELET AFFINE INVARIANT FUNCTIONS FOR SHAPE RECOGNITION. Erdem Bala, Dept. of Electrical and Computer Engineering,

COMPUTATIONALLY EFFICIENT WAVELET AFFINE INVARIANT FUNCTIONS FOR SHAPE RECOGNITION. Erdem Bala, Dept. of Electrical and Computer Engineering, COMPUTATIONALLY EFFICIENT WAVELET AFFINE INVARIANT FUNCTIONS FOR SHAPE RECOGNITION Erdem Bala, Dept. of Electrcal and Computer Engneerng, Unversty of Delaware, 40 Evans Hall, Newar, DE, 976 A. Ens Cetn,

More information

Statistics for Managers Using Microsoft Excel/SPSS Chapter 14 Multiple Regression Models

Statistics for Managers Using Microsoft Excel/SPSS Chapter 14 Multiple Regression Models Statstcs for Managers Usng Mcrosoft Excel/SPSS Chapter 14 Multple Regresson Models 1999 Prentce-Hall, Inc. Chap. 14-1 Chapter Topcs The Multple Regresson Model Contrbuton of Indvdual Independent Varables

More information

Comparison of the Population Variance Estimators. of 2-Parameter Exponential Distribution Based on. Multiple Criteria Decision Making Method

Comparison of the Population Variance Estimators. of 2-Parameter Exponential Distribution Based on. Multiple Criteria Decision Making Method Appled Mathematcal Scences, Vol. 7, 0, no. 47, 07-0 HIARI Ltd, www.m-hkar.com Comparson of the Populaton Varance Estmators of -Parameter Exponental Dstrbuton Based on Multple Crtera Decson Makng Method

More information

A Multi-Level Approach for Temporal Video Segmentation based on Adaptive Examples

A Multi-Level Approach for Temporal Video Segmentation based on Adaptive Examples June 26 2006 A Mult-Level Approach for Temporal Vdeo Segmentaton based on Adaptve Eamples Robert Babak Yeganeh Submtted to the Department of Electrcal Engneerng and Computer Scence and the Faculty of the

More information

arxiv:cs.cv/ Jun 2000

arxiv:cs.cv/ Jun 2000 Correlaton over Decomposed Sgnals: A Non-Lnear Approach to Fast and Effectve Sequences Comparson Lucano da Fontoura Costa arxv:cs.cv/0006040 28 Jun 2000 Cybernetc Vson Research Group IFSC Unversty of São

More information

Short Term Load Forecasting using an Artificial Neural Network

Short Term Load Forecasting using an Artificial Neural Network Short Term Load Forecastng usng an Artfcal Neural Network D. Kown 1, M. Km 1, C. Hong 1,, S. Cho 2 1 Department of Computer Scence, Sangmyung Unversty, Seoul, Korea 2 Department of Energy Grd, Sangmyung

More information

One-sided finite-difference approximations suitable for use with Richardson extrapolation

One-sided finite-difference approximations suitable for use with Richardson extrapolation Journal of Computatonal Physcs 219 (2006) 13 20 Short note One-sded fnte-dfference approxmatons sutable for use wth Rchardson extrapolaton Kumar Rahul, S.N. Bhattacharyya * Department of Mechancal Engneerng,

More information

A Network Intrusion Detection Method Based on Improved K-means Algorithm

A Network Intrusion Detection Method Based on Improved K-means Algorithm Advanced Scence and Technology Letters, pp.429-433 http://dx.do.org/10.14257/astl.2014.53.89 A Network Intruson Detecton Method Based on Improved K-means Algorthm Meng Gao 1,1, Nhong Wang 1, 1 Informaton

More information

Structure and Drive Paul A. Jensen Copyright July 20, 2003

Structure and Drive Paul A. Jensen Copyright July 20, 2003 Structure and Drve Paul A. Jensen Copyrght July 20, 2003 A system s made up of several operatons wth flow passng between them. The structure of the system descrbes the flow paths from nputs to outputs.

More information

An Application of Fuzzy Hypotheses Testing in Radar Detection

An Application of Fuzzy Hypotheses Testing in Radar Detection Proceedngs of the th WSES Internatonal Conference on FUZZY SYSEMS n pplcaton of Fuy Hypotheses estng n Radar Detecton.K.ELSHERIF, F.M.BBDY, G.M.BDELHMID Department of Mathematcs Mltary echncal Collage

More information

An Upper Bound on SINR Threshold for Call Admission Control in Multiple-Class CDMA Systems with Imperfect Power-Control

An Upper Bound on SINR Threshold for Call Admission Control in Multiple-Class CDMA Systems with Imperfect Power-Control An Upper Bound on SINR Threshold for Call Admsson Control n Multple-Class CDMA Systems wth Imperfect ower-control Mahmoud El-Sayes MacDonald, Dettwler and Assocates td. (MDA) Toronto, Canada melsayes@hotmal.com

More information

Color Rendering Uncertainty

Color Rendering Uncertainty Australan Journal of Basc and Appled Scences 4(10): 4601-4608 010 ISSN 1991-8178 Color Renderng Uncertanty 1 A.el Bally M.M. El-Ganany 3 A. Al-amel 1 Physcs Department Photometry department- NIS Abstract:

More information

NON-LINEAR CONVOLUTION: A NEW APPROACH FOR THE AURALIZATION OF DISTORTING SYSTEMS

NON-LINEAR CONVOLUTION: A NEW APPROACH FOR THE AURALIZATION OF DISTORTING SYSTEMS NON-LINEAR CONVOLUTION: A NEW APPROAC FOR TE AURALIZATION OF DISTORTING SYSTEMS Angelo Farna, Alberto Belln and Enrco Armellon Industral Engneerng Dept., Unversty of Parma, Va delle Scenze 8/A Parma, 00

More information

Polynomial Regression Models

Polynomial Regression Models LINEAR REGRESSION ANALYSIS MODULE XII Lecture - 6 Polynomal Regresson Models Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur Test of sgnfcance To test the sgnfcance

More information

A NEW DISCRETE WAVELET TRANSFORM

A NEW DISCRETE WAVELET TRANSFORM A NEW DISCRETE WAVELET TRANSFORM ALEXANDRU ISAR, DORINA ISAR Keywords: Dscrete wavelet, Best energy concentraton, Low SNR sgnals The Dscrete Wavelet Transform (DWT) has two parameters: the mother of wavelets

More information

Proportionate Sign Subband Adpative Filtering Algorithm for Network Echo Cancellers

Proportionate Sign Subband Adpative Filtering Algorithm for Network Echo Cancellers Journal of Advances n Computer Networks, Vol. 3, No. 2, June 2015 Proportonate Sgn Subband Adpatve Flterng Algorthm for Network Echo Cancellers J-Hye Seo, Sang Mok Jung, and Poo Gyeon Park are chosen as

More information

De-noising Method Based on Kernel Adaptive Filtering for Telemetry Vibration Signal of the Vehicle Test Kejun ZENG

De-noising Method Based on Kernel Adaptive Filtering for Telemetry Vibration Signal of the Vehicle Test Kejun ZENG 6th Internatonal Conference on Mechatroncs, Materals, Botechnology and Envronment (ICMMBE 6) De-nosng Method Based on Kernel Adaptve Flterng for elemetry Vbraton Sgnal of the Vehcle est Kejun ZEG PLA 955

More information

Analytical Chemistry Calibration Curve Handout

Analytical Chemistry Calibration Curve Handout I. Quck-and Drty Excel Tutoral Analytcal Chemstry Calbraton Curve Handout For those of you wth lttle experence wth Excel, I ve provded some key technques that should help you use the program both for problem

More information

Pulse Coded Modulation

Pulse Coded Modulation Pulse Coded Modulaton PCM (Pulse Coded Modulaton) s a voce codng technque defned by the ITU-T G.711 standard and t s used n dgtal telephony to encode the voce sgnal. The frst step n the analog to dgtal

More information

A Robust Method for Calculating the Correlation Coefficient

A Robust Method for Calculating the Correlation Coefficient A Robust Method for Calculatng the Correlaton Coeffcent E.B. Nven and C. V. Deutsch Relatonshps between prmary and secondary data are frequently quantfed usng the correlaton coeffcent; however, the tradtonal

More information

COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS

COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS Avalable onlne at http://sck.org J. Math. Comput. Sc. 3 (3), No., 6-3 ISSN: 97-537 COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS

More information

Outage Probability of Macrodiversity Reception in the Presence of Fading and Weibull Co- Channel Interference

Outage Probability of Macrodiversity Reception in the Presence of Fading and Weibull Co- Channel Interference ISSN 33-365 (Prnt, ISSN 848-6339 (Onlne https://do.org/.7559/tv-67847 Orgnal scentfc paper Outage Probablty of Macrodversty Recepton n the Presence of Fadng and Webull Co- Channel Interference Mloš PERIĆ,

More information

Scroll Generation with Inductorless Chua s Circuit and Wien Bridge Oscillator

Scroll Generation with Inductorless Chua s Circuit and Wien Bridge Oscillator Latest Trends on Crcuts, Systems and Sgnals Scroll Generaton wth Inductorless Chua s Crcut and Wen Brdge Oscllator Watcharn Jantanate, Peter A. Chayasena, and Sarawut Sutorn * Abstract An nductorless Chua

More information

Boostrapaggregating (Bagging)

Boostrapaggregating (Bagging) Boostrapaggregatng (Baggng) An ensemble meta-algorthm desgned to mprove the stablty and accuracy of machne learnng algorthms Can be used n both regresson and classfcaton Reduces varance and helps to avod

More information

DETERMINATION OF TEMPERATURE DISTRIBUTION FOR ANNULAR FINS WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY BY HPM

DETERMINATION OF TEMPERATURE DISTRIBUTION FOR ANNULAR FINS WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY BY HPM Ganj, Z. Z., et al.: Determnaton of Temperature Dstrbuton for S111 DETERMINATION OF TEMPERATURE DISTRIBUTION FOR ANNULAR FINS WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY BY HPM by Davood Domr GANJI

More information

A Two-Level Detection Algorithm for Optical Fiber Vibration

A Two-Level Detection Algorithm for Optical Fiber Vibration PHOTOIC SESORS/ Vol. 5, o. 3, 05: 84 88 A Two-Level Detecton Algorthm for Optcal Fber Vbraton Fukun BI, uecong RE *, Hongquan QU, and Ruqng JIAG College of Informaton Engneerng, orth Chna Unversty of Technology,

More information

Copyright 2017 by Taylor Enterprises, Inc., All Rights Reserved. Adjusted Control Limits for U Charts. Dr. Wayne A. Taylor

Copyright 2017 by Taylor Enterprises, Inc., All Rights Reserved. Adjusted Control Limits for U Charts. Dr. Wayne A. Taylor Taylor Enterprses, Inc. Adjusted Control Lmts for U Charts Copyrght 207 by Taylor Enterprses, Inc., All Rghts Reserved. Adjusted Control Lmts for U Charts Dr. Wayne A. Taylor Abstract: U charts are used

More information

Identification of Linear Partial Difference Equations with Constant Coefficients

Identification of Linear Partial Difference Equations with Constant Coefficients J. Basc. Appl. Sc. Res., 3(1)6-66, 213 213, TextRoad Publcaton ISSN 29-434 Journal of Basc and Appled Scentfc Research www.textroad.com Identfcaton of Lnear Partal Dfference Equatons wth Constant Coeffcents

More information

Lab 2e Thermal System Response and Effective Heat Transfer Coefficient

Lab 2e Thermal System Response and Effective Heat Transfer Coefficient 58:080 Expermental Engneerng 1 OBJECTIVE Lab 2e Thermal System Response and Effectve Heat Transfer Coeffcent Warnng: though the experment has educatonal objectves (to learn about bolng heat transfer, etc.),

More information

DPCM Compression for Real-Time Logging While Drilling Data

DPCM Compression for Real-Time Logging While Drilling Data 28 JOURAL OF SOFTWARE, VOL. 5, O. 3, MARCH 21 DPCM Compresson for Real-Tme Loggng Whle Drllng Data Yu Zhang Modern Sgnal Processng & Communcaton Group, Insttute of Informaton Scence, Bejng Jaotong Unversty,

More information

Research on Modified Root-MUSIC Algorithm of DOA Estimation Based on Covariance Matrix Reconstruction

Research on Modified Root-MUSIC Algorithm of DOA Estimation Based on Covariance Matrix Reconstruction Sensors & ransducers, Vol. 78, Issue 9, September 04, pp. 4-8 Sensors & ransducers 04 by IFSA Publshng, S. L. http://www.sensorsportal.com Research on Modfed Root-MUSIC Algorthm of DOA Estmaton Based on

More information

The Synchronous 8th-Order Differential Attack on 12 Rounds of the Block Cipher HyRAL

The Synchronous 8th-Order Differential Attack on 12 Rounds of the Block Cipher HyRAL The Synchronous 8th-Order Dfferental Attack on 12 Rounds of the Block Cpher HyRAL Yasutaka Igarash, Sej Fukushma, and Tomohro Hachno Kagoshma Unversty, Kagoshma, Japan Emal: {garash, fukushma, hachno}@eee.kagoshma-u.ac.jp

More information

Quantitative Discrimination of Effective Porosity Using Digital Image Analysis - Implications for Porosity-Permeability Transforms

Quantitative Discrimination of Effective Porosity Using Digital Image Analysis - Implications for Porosity-Permeability Transforms 2004, 66th EAGE Conference, Pars Quanttatve Dscrmnaton of Effectve Porosty Usng Dgtal Image Analyss - Implcatons for Porosty-Permeablty Transforms Gregor P. Eberl 1, Gregor T. Baechle 1, Ralf Weger 1,

More information

A new Approach for Solving Linear Ordinary Differential Equations

A new Approach for Solving Linear Ordinary Differential Equations , ISSN 974-57X (Onlne), ISSN 974-5718 (Prnt), Vol. ; Issue No. 1; Year 14, Copyrght 13-14 by CESER PUBLICATIONS A new Approach for Solvng Lnear Ordnary Dfferental Equatons Fawz Abdelwahd Department of

More information

AGC Introduction

AGC Introduction . Introducton AGC 3 The prmary controller response to a load/generaton mbalance results n generaton adjustment so as to mantan load/generaton balance. However, due to droop, t also results n a non-zero

More information

COMPARING NOISE REMOVAL IN THE WAVELET AND FOURIER DOMAINS

COMPARING NOISE REMOVAL IN THE WAVELET AND FOURIER DOMAINS COMPARING NOISE REMOVAL IN THE WAVELET AND FOURIER DOMAINS Robert J. Barsant, and Jordon Glmore Department of Electrcal and Computer Engneerng The Ctadel Charleston, SC, 29407 e-mal: robert.barsant@ctadel.edu

More information

Harmonic Detection Algorithm based on DQ Axis with Fourier Analysis for Hybrid Power Filters

Harmonic Detection Algorithm based on DQ Axis with Fourier Analysis for Hybrid Power Filters Harmonc Detecton Algorthm based on DQ Axs wth Fourer Analyss for Hybrd Power Flters K-L. AREERAK Power Qualty Research Unt, School of Electrcal Engneerng Insttute of Engneerng, Suranaree Unversty of Technology

More information

Relationship between Refractive Index and Molar Concentration of Multi-Component Solutions Zhu Xingyu 1, a, Mai Tiancheng 2, b and Zhao Zilong 2, c

Relationship between Refractive Index and Molar Concentration of Multi-Component Solutions Zhu Xingyu 1, a, Mai Tiancheng 2, b and Zhao Zilong 2, c Advances n Computer Scence Research, volume 71 4th Internatonal Conference on Machnery, Materals and Informaton Technology Applcatons (ICMMITA 2016) Relatonshp between Refractve Index and Molar Concentraton

More information

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems Numercal Analyss by Dr. Anta Pal Assstant Professor Department of Mathematcs Natonal Insttute of Technology Durgapur Durgapur-713209 emal: anta.bue@gmal.com 1 . Chapter 5 Soluton of System of Lnear Equatons

More information

Grover s Algorithm + Quantum Zeno Effect + Vaidman

Grover s Algorithm + Quantum Zeno Effect + Vaidman Grover s Algorthm + Quantum Zeno Effect + Vadman CS 294-2 Bomb 10/12/04 Fall 2004 Lecture 11 Grover s algorthm Recall that Grover s algorthm for searchng over a space of sze wors as follows: consder the

More information

Statistics II Final Exam 26/6/18

Statistics II Final Exam 26/6/18 Statstcs II Fnal Exam 26/6/18 Academc Year 2017/18 Solutons Exam duraton: 2 h 30 mn 1. (3 ponts) A town hall s conductng a study to determne the amount of leftover food produced by the restaurants n the

More information

Vector Median Filter with Directional Detector for Color Image Denoising

Vector Median Filter with Directional Detector for Color Image Denoising Proceedngs of the World Congress on Engneerng 0 Vol II WCE 0 July 6-8 0 London UK Vector Medan Flter wth Drectonal Detector for Color Image Denosng Vladmr V Khryashchev Member IAENG Dens K Kuyn and Alna

More information

Uncertainty in measurements of power and energy on power networks

Uncertainty in measurements of power and energy on power networks Uncertanty n measurements of power and energy on power networks E. Manov, N. Kolev Department of Measurement and Instrumentaton, Techncal Unversty Sofa, bul. Klment Ohrdsk No8, bl., 000 Sofa, Bulgara Tel./fax:

More information

Comparison of Regression Lines

Comparison of Regression Lines STATGRAPHICS Rev. 9/13/2013 Comparson of Regresson Lnes Summary... 1 Data Input... 3 Analyss Summary... 4 Plot of Ftted Model... 6 Condtonal Sums of Squares... 6 Analyss Optons... 7 Forecasts... 8 Confdence

More information

WARPED LINEAR PREDICTION FOR IMPROVED PERCEPTUAL QUALITY IN THE SCELP LOW DELAY AUDIO CODEC (W-SCELP)

WARPED LINEAR PREDICTION FOR IMPROVED PERCEPTUAL QUALITY IN THE SCELP LOW DELAY AUDIO CODEC (W-SCELP) ARPED LINEAR PREDICION FOR IMPROVED PERCEPUAL QUALIY IN HE SCELP LO DELAY AUDIO CODEC (-SCELP) Hauke Krüger and Peter Vary Insttute of Communcaton Systems and Data Processng RH Aachen Unversty, D-5256

More information

ECE559VV Project Report

ECE559VV Project Report ECE559VV Project Report (Supplementary Notes Loc Xuan Bu I. MAX SUM-RATE SCHEDULING: THE UPLINK CASE We have seen (n the presentaton that, for downlnk (broadcast channels, the strategy maxmzng the sum-rate

More information

A New Metric for Quality Assessment of Digital Images Based on Weighted-Mean Square Error 1

A New Metric for Quality Assessment of Digital Images Based on Weighted-Mean Square Error 1 A New Metrc for Qualty Assessment of Dgtal Images Based on Weghted-Mean Square Error Proceedngs of SPIE, vol. 4875, 2002 Kawen Zhang, Shuozhong Wang, and Xnpen Zhang School of Communcaton and Informaton

More information

Comparative Analysis between Different Linear Filtering Algorithms of Gamma Ray Spectroscopy

Comparative Analysis between Different Linear Filtering Algorithms of Gamma Ray Spectroscopy Comparatve Analyss between Dfferent Lnear Flterng Algorthms of Gamma Ray Spectroscopy Mohamed S. El_Tokhy, Imbaby I. Mahmoud, and Hussen A. Konber Abstract Ths paper presents a method to evaluate and mprove

More information

The Order Relation and Trace Inequalities for. Hermitian Operators

The Order Relation and Trace Inequalities for. Hermitian Operators Internatonal Mathematcal Forum, Vol 3, 08, no, 507-57 HIKARI Ltd, wwwm-hkarcom https://doorg/0988/mf088055 The Order Relaton and Trace Inequaltes for Hermtan Operators Y Huang School of Informaton Scence

More information

Suppose that there s a measured wndow of data fff k () ; :::; ff k g of a sze w, measured dscretely wth varable dscretzaton step. It s convenent to pl

Suppose that there s a measured wndow of data fff k () ; :::; ff k g of a sze w, measured dscretely wth varable dscretzaton step. It s convenent to pl RECURSIVE SPLINE INTERPOLATION METHOD FOR REAL TIME ENGINE CONTROL APPLICATIONS A. Stotsky Volvo Car Corporaton Engne Desgn and Development Dept. 97542, HA1N, SE- 405 31 Gothenburg Sweden. Emal: astotsky@volvocars.com

More information

Integrating Neural Networks and PCA for Fast Covert Surveillance

Integrating Neural Networks and PCA for Fast Covert Surveillance Integratng Neural Networks and PCA for Fast Covert Survellance Hazem M. El-Bakry, and Mamoon H. Mamoon Faculty of Computer Scence & Informaton Systems, Mansoura Unversty, EGYPT E-mal: helbakry0@yahoo.com

More information

Over-Temperature protection for IGBT modules

Over-Temperature protection for IGBT modules Over-Temperature protecton for IGBT modules Ke Wang 1, Yongjun Lao 2, Gaosheng Song 1, Xanku Ma 1 1 Mtsubsh Electrc & Electroncs (Shangha) Co., Ltd., Chna Room2202, Tower 3, Kerry Plaza, No.1-1 Zhongxns

More information

Power law and dimension of the maximum value for belief distribution with the max Deng entropy

Power law and dimension of the maximum value for belief distribution with the max Deng entropy Power law and dmenson of the maxmum value for belef dstrbuton wth the max Deng entropy Bngy Kang a, a College of Informaton Engneerng, Northwest A&F Unversty, Yanglng, Shaanx, 712100, Chna. Abstract Deng

More information

Lecture 6: Introduction to Linear Regression

Lecture 6: Introduction to Linear Regression Lecture 6: Introducton to Lnear Regresson An Manchakul amancha@jhsph.edu 24 Aprl 27 Lnear regresson: man dea Lnear regresson can be used to study an outcome as a lnear functon of a predctor Example: 6

More information

Modal Strain Energy Decomposition Method for Damage Detection of an Offshore Structure Using Modal Testing Information

Modal Strain Energy Decomposition Method for Damage Detection of an Offshore Structure Using Modal Testing Information Thrd Chnese-German Jont Symposum on Coastal and Ocean Engneerng Natonal Cheng Kung Unversty, Tanan November 8-16, 2006 Modal Stran Energy Decomposton Method for Damage Detecton of an Offshore Structure

More information

Number of cases Number of factors Number of covariates Number of levels of factor i. Value of the dependent variable for case k

Number of cases Number of factors Number of covariates Number of levels of factor i. Value of the dependent variable for case k ANOVA Model and Matrx Computatons Notaton The followng notaton s used throughout ths chapter unless otherwse stated: N F CN Y Z j w W Number of cases Number of factors Number of covarates Number of levels

More information

Mixed Noise Suppression in Color Images by Signal-Dependent LMS L-Filters

Mixed Noise Suppression in Color Images by Signal-Dependent LMS L-Filters 46 R. HUDEC MIXED OISE SUPPRESSIO I COLOR IMAGES BY SIGAL-DEPEDET LMS L-FILTERS Mxed ose Suppresson n Color Images by Sgnal-Dependent LMS L-Flters Róbert HUDEC Dept. of Telecommuncatons Unversty of Žlna

More information

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system Transfer Functons Convenent representaton of a lnear, dynamc model. A transfer functon (TF) relates one nput and one output: x t X s y t system Y s The followng termnology s used: x y nput output forcng

More information

Support Vector Machines. Vibhav Gogate The University of Texas at dallas

Support Vector Machines. Vibhav Gogate The University of Texas at dallas Support Vector Machnes Vbhav Gogate he Unversty of exas at dallas What We have Learned So Far? 1. Decson rees. Naïve Bayes 3. Lnear Regresson 4. Logstc Regresson 5. Perceptron 6. Neural networks 7. K-Nearest

More information

THE EFFECT OF TORSIONAL RIGIDITY BETWEEN ELEMENTS ON FREE VIBRATIONS OF A TELESCOPIC HYDRAULIC CYLINDER SUBJECTED TO EULER S LOAD

THE EFFECT OF TORSIONAL RIGIDITY BETWEEN ELEMENTS ON FREE VIBRATIONS OF A TELESCOPIC HYDRAULIC CYLINDER SUBJECTED TO EULER S LOAD Journal of Appled Mathematcs and Computatonal Mechancs 7, 6(3), 7- www.amcm.pcz.pl p-issn 99-9965 DOI:.75/jamcm.7.3. e-issn 353-588 THE EFFECT OF TORSIONAL RIGIDITY BETWEEN ELEMENTS ON FREE VIBRATIONS

More information

On the Repeating Group Finding Problem

On the Repeating Group Finding Problem The 9th Workshop on Combnatoral Mathematcs and Computaton Theory On the Repeatng Group Fndng Problem Bo-Ren Kung, Wen-Hsen Chen, R.C.T Lee Graduate Insttute of Informaton Technology and Management Takmng

More information

AN ADAPTIVE WATERMARKING ALGORITHM FOR DEM BASED ON DFT

AN ADAPTIVE WATERMARKING ALGORITHM FOR DEM BASED ON DFT AN ADAPTIVE WATERMARKING ALGORITHM FOR DEM BASED ON DFT Changqng Zhu 1 Zhwe Wang 2 Y Long 1 Chengsong Yang 2 1 Key Laboratory of Vrtual Geographc Envronment, Nanjng Normal Unversty, Nanjng 210054;2 Insttute

More information

Research Article Green s Theorem for Sign Data

Research Article Green s Theorem for Sign Data Internatonal Scholarly Research Network ISRN Appled Mathematcs Volume 2012, Artcle ID 539359, 10 pages do:10.5402/2012/539359 Research Artcle Green s Theorem for Sgn Data Lous M. Houston The Unversty of

More information

An Admission Control Algorithm in Cloud Computing Systems

An Admission Control Algorithm in Cloud Computing Systems An Admsson Control Algorthm n Cloud Computng Systems Authors: Frank Yeong-Sung Ln Department of Informaton Management Natonal Tawan Unversty Tape, Tawan, R.O.C. ysln@m.ntu.edu.tw Yngje Lan Management Scence

More information

ANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U)

ANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U) Econ 413 Exam 13 H ANSWERS Settet er nndelt 9 deloppgaver, A,B,C, som alle anbefales å telle lkt for å gøre det ltt lettere å stå. Svar er gtt . Unfortunately, there s a prntng error n the hnt of

More information

A New Adaptive Filter Approach for Acoustic Echo Canceller in Teleconference Systems

A New Adaptive Filter Approach for Acoustic Echo Canceller in Teleconference Systems European Scentfc Journal September 28 edton Vol4 No27 ISSN: 857 788 (rnt) e - ISSN 857-743 A New Adaptve Flter Approach for Acoustc Echo Canceller n eleconference Systems Hamze Hadar Alaeddne Al Beydoun

More information

Simulated Power of the Discrete Cramér-von Mises Goodness-of-Fit Tests

Simulated Power of the Discrete Cramér-von Mises Goodness-of-Fit Tests Smulated of the Cramér-von Mses Goodness-of-Ft Tests Steele, M., Chaselng, J. and 3 Hurst, C. School of Mathematcal and Physcal Scences, James Cook Unversty, Australan School of Envronmental Studes, Grffth

More information

Chapter 5 Multilevel Models

Chapter 5 Multilevel Models Chapter 5 Multlevel Models 5.1 Cross-sectonal multlevel models 5.1.1 Two-level models 5.1.2 Multple level models 5.1.3 Multple level modelng n other felds 5.2 Longtudnal multlevel models 5.2.1 Two-level

More information

Department of Quantitative Methods & Information Systems. Time Series and Their Components QMIS 320. Chapter 6

Department of Quantitative Methods & Information Systems. Time Series and Their Components QMIS 320. Chapter 6 Department of Quanttatve Methods & Informaton Systems Tme Seres and Ther Components QMIS 30 Chapter 6 Fall 00 Dr. Mohammad Zanal These sldes were modfed from ther orgnal source for educatonal purpose only.

More information

Novel Pre-Compression Rate-Distortion Optimization Algorithm for JPEG 2000

Novel Pre-Compression Rate-Distortion Optimization Algorithm for JPEG 2000 Novel Pre-Compresson Rate-Dstorton Optmzaton Algorthm for JPEG 2000 Yu-We Chang, Hung-Ch Fang, Chung-Jr Lan, and Lang-Gee Chen DSP/IC Desgn Laboratory, Graduate Insttute of Electroncs Engneerng Natonal

More information

MACHINE APPLIED MACHINE LEARNING LEARNING. Gaussian Mixture Regression

MACHINE APPLIED MACHINE LEARNING LEARNING. Gaussian Mixture Regression 11 MACHINE APPLIED MACHINE LEARNING LEARNING MACHINE LEARNING Gaussan Mture Regresson 22 MACHINE APPLIED MACHINE LEARNING LEARNING Bref summary of last week s lecture 33 MACHINE APPLIED MACHINE LEARNING

More information

System in Weibull Distribution

System in Weibull Distribution Internatonal Matheatcal Foru 4 9 no. 9 94-95 Relablty Equvalence Factors of a Seres-Parallel Syste n Webull Dstrbuton M. A. El-Dacese Matheatcs Departent Faculty of Scence Tanta Unversty Tanta Egypt eldacese@yahoo.co

More information