This is the first book to introduce and integrate the topics of digital signal processing (DSP) and statistical classification together, and the only volume to introduce stateoftheart transforms, including DFT, FFT, DCT, DST, DHT, DHLT, DFHT, DTWT, DWT, DHAT, PCT, CCT, CDT, and ODT together for DSP and digital communication applications. You get stepbystep guidance in: discretetime random processes; discretetime domain signal processing and frequency domain signal analysis; discretetime transforms; digital filter design and adaptive filtering; multirate digital signal processing; and statistical signal classification. The text also helps you overcome problems associated with multirate A/D and D/A converters. Extensively referenced with over 1,065 equations, 142 illustrations, and numerous examples, the book furnishes an uptodate, comprehensive, and coherent treatment of the fundamentals of this cuttingedge technology, based on the academic and industry experience of the authors. An excellent technical reference and research tool for both practicing engineers and graduate students in electrical, computer, and other engineering disciplines, this book offers assistance in applying DSP knowledge and statistical classification in real world applications. This authoritative volume includes critical concepts never before covered in this detail.
About the Authors; Preface; IntroductionData Acquisition System. DSP Algorithms. Statistical Signal Classification. Scope of This Book. References.; DiscreteTime Signal ProcessingIntroduction. DiscreteTime Signals. Basic Operations of DiscreteTime Signals. DiscreteTime Systems. Linear TimeInvariant DiscreteTime Systems. The zTransform. The Inverse zTransform. Frequency Domain of DiscreteTime Signals and Systems. The Relationship of Allpass and MinimumPhase Systems. Summary. References.; DiscreteTime Random ProcessesIntroduction. Probability and Random Variables. Distribution and Density Functions. Stochastic Processes. Summary. References.; DiscreteTime TransformsIntroduction. The Discrete Fourier Transform. The Fast Fourier Transform. The Discrete Cosine Transform. The Discrete Sine Transforms. The Discrete Hartley Transform. The Discrete Hilbert Transform. The Discrete Fractional Hilbert Transform. The DiscreteTime Wavelet Transform. The Discrete Walsh Transform. The Discrete Hadamard Transform. Summary. References.; Digital FilteringIntroduction. Filter Specifications. FIR Linear Phase. FIR Filter Design. IIR Filter Design. Implementation of Filter Structures. Summary. References.; Adaptive FiltersIntroduction. Wiener Filter Theory. DiscreteTime Kalman Filter. The LMS Adaptive Filters. Recursive Least Squares Algorithms. Summary. References.; DiscreteTime Multirate Signal ProcessingIntroduction. Decimation and Interpolation System. Efficient Polyphase Architecture for Implementing Multirate Signal Processing System. Efficient Design Techniques of Multiband Filters. Multistage Design of Multirate Signal Processing. Multirate Filter Banks. The Uniform DFT Filter Bank. Multirate Adaptive Filter Banks. Summary. References.; Multirate Data ConvertersIntroduction. AnalogToDigital Converter. DigitalToAnalog Converter. Multirate A/D Converter. Multirate D/A Converter. Oversampling A/D Converters. SigmaDelta A/D Converter. Hybrid QMF Bank A/D and D/A Converter. Summary. References.; Statistical Signal ClassificationIntroduction. Statistical Pattern Representation. Feature Extraction Theory. Unsupervised Learning and Cluster Analysis. Signal Classification. Estimated Probability of Misclassification. Summary. References.; TransformBased Statistical Signal ClassificationIntroduction. System Architectures of TransformBased Statistical Signal Classification. Generalized Principal Components Transform. Canonical Correlation Transform. Canonical Discrimination Transform. Optimal Discriminant Transform.; Generalized Optimal Declustering Transform. TransformBased Statistical Signal Classifiers. Application and Performance Evaluations. Summary. References.; Appendix AMatrix Algebra of Linear Transformation. Vectors. Matrices. The Data Matrix. Orthogonal Matrices and the Trace. Matrix Differentiation. Eigenvalues and Eigenvectors. Theorem of Spectral Decomposition. Theorem of Singular Value Decomposition. Quadratic Forms. Maximization and Minimization Theorem. References.; List of Figures.; Index.;

Mark A. Clements
Mark A. Clements is a professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology, and director of the Interactive Media Technology Center. He holds B.S., S.M., E.E., and Sc.D. degrees, all in Electrical Engineering and Computer Science, from the Massachusetts Institute of Technology. He has published over 100 technical papers and holds several U.S. patents. He is also the coauthor of Objective Measures of Speech Quality (Prentice Hall, 1988). He has served as a member of the IEEE Speech Technical Committee and has been an Associate Editor for speech in IEEE Transactions on Speech and Audio. Dr. Clements was technical program cochairman of Speech Tech in 1986, and Technical Program Chair of the IEEE ICASSP in 1996.

George J. Miao
George J. Miao is a president of Sageco Technologies, LLC. He specializes in digital signal processing, multirate, adaptive and statistical signal processing theory with applications in wireless/wireline communication systems design, simulation modeling, and architecture. His extensive professional experience includes work for Motorola, Fujitsu Network Communications, HewlettPackard, Intel, and Lockheed Martin. He is coauthor of 'Digital Signal Processing and Statistical Classification'ù (Artech House, 2002), for which he received the 2003 IEEE New Jersey Coast Section Technical Accomplishment Award. He has published many articles in journals and conferences, and holds US patents and patents pending in wireless, wireline and UWB communications. He holds an M.Sc. from Columbia University and a Ph.D. from the Georgia Institute of Technology, both in electrical engineering.