LEADER 05594nam 22007214a 450 001 9910146252003321 005 20210209155234.0 010 $a0-470-61238-X 010 $a1-280-51059-5 010 $a9786610510597 010 $a1-84704-463-8 010 $a0-470-39452-8 010 $a1-84704-563-4 035 $a(CKB)1000000000469417 035 $a(EBL)700731 035 $a(OCoLC)156938589 035 $a(SSID)ssj0000139180 035 $a(PQKBManifestationID)11147726 035 $a(PQKBTitleCode)TC0000139180 035 $a(PQKBWorkID)10010594 035 $a(PQKB)10661531 035 $a(MiAaPQ)EBC700731 035 $a(CaSebORM)9781905209132 035 $a(MiAaPQ)EBC261401 035 $a(Au-PeEL)EBL261401 035 $a(OCoLC)936815276 035 $a(EXLCZ)991000000000469417 100 $a20060414d2006 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aDigital signal and image processing using Matlab$b[electronic resource] /$fGe?rard Blanchet, Maurice Charbit 205 $a1st edition 210 $aLondon ;$aNewport Beach, CA $cISTE Ltd.$dc2006 215 $a1 online resource (765 p.) 225 1 $aDigital signal and image processing series 300 $aTranslation of: Signaux et images sous Matlab. 311 $a1-905209-13-4 320 $aIncludes bibliographical references (p. [739]-746) and index. 327 $aDigital Signal and Image Processing using MATLAB; Contents; Preface; Notations and Abbreviations; Introduction to MATLAB; 1 Variables; 1.1 Vectors and matrices; 1.2 Arrays; 1.3 Cells and structures; 2 Operations and functions; 2.1 Matrix operations; 2.2 Pointwise operations; 2.3 Constants and initialization; 2.4 Predefined matrices; 2.5 Mathematical functions; 2.6 Matrix functions; 2.7 Other useful functions; 2.8 Logical operators on boolean variables; 2.9 Program loops; 3 Graphically displaying results; 4 Converting numbers to character strings; 5 Input/output; 6 Program writing 327 $aPart I Deterministic SignalsChapter 1 Signal Fundamentals; 1.1 The concept of signal; 1.1.1 A few signals; 1.1.2 Spectral representation of signals; 1.2 The Concept of system; 1.3 Summary; Chapter 2 Discrete Time Signals and Sampling; 2.1 The sampling theorem; 2.1.1 Perfect reconstruction; 2.1.2 Digital-to-analog conversion; 2.2 Plotting a signal as a function of time; 2.3 Spectral representation; 2.3.1 Discrete-time Fourier transform (DTFT); 2.3.2 Discrete Fourier transform (DFT); 2.4 Fast Fourier transform; Chapter 3 Spectral Observation; 3.1 Spectral accuracy and resolution 327 $a3.1.1 Observation of a complex exponential3.1.2 Plotting accuracy of the DTFT; 3.1.3 Frequency resolution; 3.1.4 Effects of windowing on the resolution; 3.2 Short term Fourier transform; 3.3 Summing up; 3.4 Application examples and exercises; 3.4.1 Amplitude modulations; 3.4.2 Frequency modulation; Chapter 4 Linear Filters; 4.1 Definitions and properties; 4.2 The z-transform; 4.2.1 Definition and properties; 4.2.2 A few examples; 4.3 Transforms and linear filtering; 4.4 Difference equations and rational TF filters; 4.4.1 Stability considerations; 4.4.2 FIR and IIR filters 327 $a4.4.3 Causal solution and initial conditions4.4.4 Calculating the responses; 4.4.5 Stability and the Jury test; 4.5 Connection between gain and poles/zeros; 4.6 Minimum phase filters; 4.7 Filter design methods; 4.7.1 Going from the continuous-time filter to the discretetime filter; 4.7.2 FIR filter design using the window method; 4.7.3 IIR filter design; 4.8 Oversampling and undersampling; 4.8.1 Oversampling; 4.8.2 Undersampling; Chapter 5 Filter Implementation; 5.1 Filter implementation; 5.1.1 Examples of filter structures; 5.1.2 Distributing the calculation load in an FIR filter 327 $a5.1.3 FIR block filtering5.1.4 FFT filtering; 5.2 Filter banks; 5.2.1 Decimation and expansion; 5.2.2 Filter banks; Chapter 6 An Introduction to Image Processing; 6.1 Introduction; 6.1.1 Image display, color palette; 6.1.2 Importing images; 6.1.3 Arithmetical and logical operations; 6.2 Geometric transformations of an image; 6.2.1 The typical transformations; 6.2.2 Aligning images; 6.3 Frequential content of an image; 6.4 Linear filtering; 6.5 Other operations on images; 6.5.1 Undersampling; 6.5.2 Oversampling; 6.5.3 Contour detection; 6.5.4 Median filtering; 6.5.5 Maximum enhancement 327 $a6.5.6 Image binarization 330 $aThis title provides the most important theoretical aspects of Image and Signal Processing (ISP) for both deterministic and random signals. The theory is supported by exercises and computer simulations relating to real applications.More than 200 programs and functions are provided in the MATLABŪ language, with useful comments and guidance, to enable numerical experiments to be carried out, thus allowing readers to develop a deeper understanding of both the theoretical and practical aspects of this subject. 410 0$aDigital signal and image processing series. 606 $aSignal processing$xDigital techniques$xData processing 608 $aElectronic books. 615 0$aSignal processing$xDigital techniques$xData processing. 676 $a621.382/2 676 $a621.3822 700 $aBlanchet$b Gerard$0848441 701 $aCharbit$b Maurice$030777 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910146252003321 996 $aDigital signal and image processing using Matlab$92252767 997 $aUNINA LEADER 04037nam 22007335 450 001 9910917782703321 005 20250807143408.0 010 $a9789819752317 010 $a9819752310 024 7 $a10.1007/978-981-97-5231-7 035 $a(MiAaPQ)EBC31837011 035 $a(Au-PeEL)EBL31837011 035 $a(CKB)37018353000041 035 $a(DE-He213)978-981-97-5231-7 035 $a(OCoLC)1484073246 035 $a(EXLCZ)9937018353000041 100 $a20241214d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aProceedings of 4th International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication $eMARC 2023, Volume 2 /$fedited by Anuradha Tomar, Sukumar Mishra, Y. R. Sood, Pramod Kumar 205 $a1st ed. 2024. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2024. 215 $a1 online resource (399 pages) 225 1 $aLecture Notes in Electrical Engineering,$x1876-1119 ;$v1232 311 08$a9789819752300 311 08$a9819752302 327 $aDetecting Alternaria Solani in Tomatoes: Identification with VGG-19 Deep Learning for Early Detection -- Image Encryption Technique using S-box and Discrete Cosine Transform -- Enhancing Power Quality in Grid-Tied Solar Photovoltaic Systems -- RF-TSVM: Random Forest based Transductive Support Vector Machine for Classification and Prediction of Cancer Patterns -- Resource-Efficient Image Retrieval: A Study of Local Patterns vs. Deep Learning Models -- Machine Translation of Chinese Hindi Simple Sentences using Moses -- Innovative Approaches to Reduce Carbon Footprint and Air Pollution: The Role of AI, ML, Cloud Computing, and IoT -- Investigating Sensor Technology and benefits of Intelligent Transport Systems -- Student Attendance System using QR code Analysis of Brain tumor detection using Machine Learning -- A Review on Multiple Face Detection Techniques and Challenges -- Blockchain-Enabled Secure Identity Verification in Agri-food Supply Chain -- Machine Learning Approach for Diagnosis of Schizophrenia using EEG Signals -- Comparative Analysis Of Web Apis:Restful And Graphql -- Ai-Based Vision Screening Tool For Keratoconus. 330 $aThis book gathers selected papers presented at International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication (MARC 2023), held in Glocal University, Saharanpur, Uttar Pradesh, India, during 28?29 November 2023. This book discusses key concepts, challenges, and potential solutions in connection with established and emerging topics in advanced computing, renewable energy, and network communications. 410 0$aLecture Notes in Electrical Engineering,$x1876-1119 ;$v1232 606 $aComputational intelligence 606 $aInternet of things 606 $aPower electronics 606 $aRenewable energy sources 606 $aMachine learning 606 $aComputational Intelligence 606 $aInternet of Things 606 $aPower Electronics 606 $aRenewable Energy 606 $aMachine Learning 615 0$aComputational intelligence. 615 0$aInternet of things. 615 0$aPower electronics. 615 0$aRenewable energy sources. 615 0$aMachine learning. 615 14$aComputational Intelligence. 615 24$aInternet of Things. 615 24$aPower Electronics. 615 24$aRenewable Energy. 615 24$aMachine Learning. 676 $a006.31 700 $aTomar$b Anuradha$01434333 701 $aMishra$b Sukumar$01779997 701 $aSood$b Y. 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