ABSTRACT

Signal Processing: A Mathematical Approach is designed to show how many of the mathematical tools the reader knows can be used to understand and employ signal processing techniques in an applied environment. Assuming an advanced undergraduate- or graduate-level understanding of mathematics-including familiarity with Fourier series, matrices, probab

chapter 1|16 pages

Introduction

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chapter 2|30 pages

Fourier Series and Fourier Transforms

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chapter 3|26 pages

Remote Sensing

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chapter 4|18 pages

Finite-Parameter Models

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chapter 5|12 pages

Transmission and Remote Sensing

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chapter 6|8 pages

The Fourier Transform and Convolution Filtering

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chapter 7|8 pages

Infinite Sequences and Discrete Filters

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chapter 8|14 pages

Convolution and the Vector DFT

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chapter 9|18 pages

Plane-Wave Propagation

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chapter 10|8 pages

The Phase Problem

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chapter 11|10 pages

Transmission Tomography

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chapter 12|24 pages

Random Sequences

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chapter 13|32 pages

Nonlinear Methods

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chapter 14|8 pages

Discrete Entropy Maximization

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chapter 15|16 pages

Analysis and Synthesis

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chapter 16|16 pages

Wavelets

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chapter 17|16 pages

The BLUE and the Kalman Filter

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chapter 18|10 pages

1 The Model of Signal in Additive Noise

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chapter 19|12 pages

Inner Products

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chapter 20|12 pages

Wiener Filtering

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chapter 21|20 pages

Matrix Theory

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chapter 22|14 pages

Compressed Sensing

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chapter 23|16 pages

Probability

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chapter 24|12 pages

Using the Wave Equation

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chapter 25|6 pages

Reconstruction in Hilbert Space

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chapter 26|8 pages

Some Theory of Fourier Analysis

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chapter 27|6 pages

Reverberation and Echo Cancellation

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