Orthogonal Transforms for Digital Signal Processing
Autor N. Ahmed, K. R. Raoen Limba Engleză Paperback – 23 feb 2012
Preț: 375.08 lei
Puncte Express: 563
Carte tipărită la comandă
Livrare economică 11-25 iulie
Livrare prin curier în România Termenul estimat este afișat lângă disponibilitate.
Transport gratuit de la 400.00 lei Plată online sau ramburs, în funcție de opțiunile comenzii.
Retur gratuit în 14 zile Comandă securizată și suport în română.
Specificații
ISBN-13: 9783642454523
ISBN-10: 3642454526
Pagini: 276
Ilustrații: XII, 264 p.
Dimensiuni: 155 x 235 x 16 mm
Greutate: 0.42 kg
Ediția:Softcover reprint of the original 1st ed. 1975
Editura: Springer
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3642454526
Pagini: 276
Ilustrații: XII, 264 p.
Dimensiuni: 155 x 235 x 16 mm
Greutate: 0.42 kg
Ediția:Softcover reprint of the original 1st ed. 1975
Editura: Springer
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
One Introduction.- 1.1 General Remarks.- 1.2 Terminology.- 1.3 Signal Representation Using Orthogonal Functions.- 1.4 Book Outline.- References.- Problems.- Two Fourier Representation of Signals.- 2.1 Fourier Representation.- 2.2 Power, Amplitude, and Phase Spectra.- 2.3 Fourier Transform.- 2.4 Relation Between the Fourier Series and the Fourier Transform.- 2.5 Crosscorrelation, Autocorrelation, and Convolution.- 2.6 Sampling Theorem.- 2.7 Summary.- References.- Problems.- Three Fourier Representation of Sequences.- 3.1 Definition of the Discrete Fourier Transform.- 3.2 Properties of the DFT.- 3.3 Matrix Representation of Correlation and Convolution.- 3.4 Relation Between the DFT and the Fourier Transform Series.- 3.5 Power, Amplitude, and Phase Spectra.- 3.6 2-dimensional DFT.- 3.7 Time-varying Fourier Spectra.- 3.8 Summary.- Appendix 3.1.- References.- Problems.- Four Fast Fourier Transform.- 4.1 Statement of the Problem.- 4.2 Motivation to Search for an Algorithm.- 4.3 Key to Developing the Algorithm.- 4.4 Development of the Algorithm.- 4.5 Illustrative Examples.- 4.6 Shuffling.- 4.7 Operations Count and Storage Requirements.- 4.8 Some Applications.- 4.9 Summary.- Appendix 4.1 An FFT Computer Program.- References.- Problems.- Five A Class of Orthogonal Functions.- 5.1 Definition of Sequency.- 5.2 Notation.- 5.3 Rademacher and Haar Functions.- 5.4 Walsh Functions.- 5.5 Summary.- Appendix 5.1 Elements of the Gray Code.- References.- Problems.- Six Walsh-Hadamard Transform.- 6.1 Walsh Series Representation.- 6.2 Hadamard Ordered Walsh-Hadamard Transform (WHT)h.- 6.3 Fast Hadamard Ordered Walsh-Hadamard Transform (FWHT)h.- 6.4 Walsh Ordered Walsh-Hadamard Transform (WHT)W.- 6.5 Fast Walsh Ordered Walsh-Hadamard Transform (FWHT)w.- 6.6 Cyclic and Dyadic Shifts.- 6.7 (WHT)w Spectra.- 6.8 (WHT)h Spectra.- 6.9 Physical Interpretations for the (WHT)h Power Spectrum.- 6.10 Modified Walsh-Hadamard Transform (MWHT).- 6.11 Cyclic and Dyadic Correlation/Convolution.- 6.12 Multidimensional (WHT)h and (WHT)w.- 6.13 Summary.- Appendix 6.1 WHT Computer Program.- References.- Problems.- Seven Miscellaneous Orthogonal Transforms.- 7.1 Matrix Factorization.- 7.2 Generalized Transform.- 7.3 Haar Transform.- 7.4 Algorithms to Compute the HT.- 7.5 Slant Matrices.- 7.6 Definition of the Slant Transform (ST).- 7.7 Discrete Cosine Transform (DCT).- 7.8 2-dimensional Transform Considerations.- 7.9 Summary.- Appendix 7.1 Kronecker Products.- Appendix 7.2 Matrix Factorization.- References.- Problems.- Eight Generalized Wiener Filtering.- 8.1 Some Basic Matrix Operations.- 8.2 Mathematical Model.- 8.3 Filter Design.- 8.4 Suboptimal Wiener Filtering.- 8.5 Optimal Diagonal Filters.- 8.6 Suboptimal Diagonal Filters.- 8.7 2-dimensional Wiener Filtering Considerations.- 8.8 Summary.- Appendix 8.1 Some Terminology and Definitions.- References.- Problems.- Nine Data Compression.- 9.1 Search for the Optimum Transform.- 9.2 Variance Criterion and the Variance Distribution.- 9.3 Electrocardiographic Data Compression.- 9.4 Image Data Compression Considerations.- 9.5 Image Data Compression Examples.- 9.6 Additional Considerations.- 9.7 Summary.- Appendix 9.1 Lagrange Multipliers.- References.- Problems.- Ten Feature Selection in Pattern Recognition.- 10.1 Introduction.- 10.2 The Concept of Training.- 10.3 d-Dimensional Patterns.- 10.4 The 3-Class Problem.- 10.5 Image Classification Experiment.- 10.6 Least-Squares Mapping Technique.- 10.7 Augmented Feature Space.- 10.8 3-Class Least-Squares Minimum Distance Classifier.- 10.9 K-Class Least-Squares Minimum Distance Classifier.- 10.10 Quadratic Classifiers.- 10.11 An ECG Classification Experiment.- 10.12 Summary.- References.- Problems.- Author Index.