# Algorithms for statistical signal processing

Material type: TextPublication details: Delhi : Pearson Education., 2002Description: xii, 564 p. : illustrationsISBN: 0130622192 ; 9780130622198; 8178085739 ; 9788178085739 Subject(s): Signal processing - Digital techniques - Mathematics | Algorithms | Digital signal processing | Statistics | Statistical news theory | Stochastic signalDDC classification: 005.1Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds |
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Reference Books | Main Library Reference | Reference | 005.1 ALG (Browse shelf(Opens below)) | Available | 008556 |

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Included Index.

Characterization of Signals --

Characterization of Linear Time-Invariant Systems --

Sampling of Signals --

Linear Filtering Methods Based on the DFT --

The Cepstrum --

Algorithms for Convolution and Dft --

Modulo Polynomials --

Circular Convolution as Polynomial Multiplication mod u[superscript N]--1 --

A Continued Fraction of Polynomials --

Chinese Remainder Theorem for Polynomials --

Algorithms for Short Circular Convolutions --

How We Count Multiplications --

Cyclotomic Polynomials --

Elementary Number Theory --

Convolution Length and Dimension --

The DFT as a Circular Convolution --

Winograd's DFT Algorithm --

Number-Theoretic Analogy of DFT --

Number-Theoretic Transform --

Split-Radix FFT --

Autogen Technique --

Linear Prediction and Optimum Linear Filters --

Innovations Representation of a Stationary Random Process --

Forward and Backward Linear Prediction --

Solution of the Normal Equations --

Properties of the Linear Prediction-Error Filters --

AR Lattice and ARMA Lattice-Ladder Filters --

Wiener Filters for Filtering and Prediction --

Least-Squares Methods for System Modeling and Filter Design --

System Modeling and Identification --

Least-Squares Filter Design for Prediction and Deconvolution --

Solution of Least-Squares Estimation Problems --

Adaptive Filters --

Applications of Adaptive Filters --

Adaptive Direct-Form FIR Filters --

Adaptive Lattice-Ladder Filters --

Recursive Least-Squares Algorithms for Array Signal Processing --

QR Decomposition for Least-Squares Estimation.

Suitable for graduate-level courses in Digital Signal Processing in ECE and applied mathematics departments. This presentation of computational algorithms for statistical signal processing focuses on advanced topics, such as algorithms for adaptive filtering, least squares methods, power spectrum estimation, and high-order spectral estimation.

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