Digital Signal Processing using MATLAB – John G. Proakis – 3rd Edition

In this supplementary text, MATLAB is used as a computing tool to explore traditional DSP topics and solve problems to gain insight. This greatly expands the range and complexity of problems that students can effectively study in the course. Since DSP applications are primarily algorithms implemented on a DSP processor or software, a fair amount of programming is required.

Using interactive software such as MATLAB makes it possible to place more emphasis on learning new and difficult concepts than on programming algorithms. Interesting practical examples are discussed and useful problems are explored.

1. INTRODUCTION.
Overview of . A Brief Introduction to MATLAB®. Applications of . Brief Overview of the Book.

2. DISCRETE-TIME SIGNALS AND SYSTEMS.
Discrete-time Signals. Discrete Systems. Convolution. Difference .

3. THE DISCRETE-TIME FOURIER ANALYSIS.
The Discrete-time Fourier Transform (DTFT). The Properties of the DTFT. The Domain Representation of LTI Systems. Sampling and Reconstruction of Analog Signals.

4. THE z-TRANSFORM.
The Bilateral z-Transform. Important Properties of the z-Transform. Inversion of the z-Transform. System Representation in the z-Domain. Solutions of the Difference Equations.

5. THE DISCRETE FOURIER TRANSFORM.
The Discrete Fourier . Sampling and Reconstruction in the z-Domain. The Discrete Fourier Transform. Properties of the Discrete Fourier Transform. Linear Convolution Using the DFT. The Fast Fourier Transform.

6. IMPLEMENTATION OF DISCRETE-TIME FILTERS.
Basic . IIR Filter Structures. FIR Filter Structures. Lattice Filter Structures. Overview of Finite-Precision Numerical Effects. Representation of Numbers. The Process of Quantization and Error Characterizations. Quantization of Filter Coefficients.

7. FIR FILTER DESIGN.
Preliminaries. Properties of Linear-phase FIR Filters. Window Design Techniques. Optimal Equiripple Design Technique.

8. IIR FILTER DESIGN.
Some Preliminaries. Some Special Filter Types. Characteristics of Prototype Analog Filters. Analog-to-Digital Filter Transformations. Lowpass Filter Design Using MATLAB®. Frequency-band Transformations.

9. SAMPLING RATE CONVERSION.
Introduction. Decimation by a Factor D. Interpolation by a Factor I. Sampling Rate Conversion by a Rational Factor I/D. FIR Filter Designs for Sampling Rate Conversion. FIR Filter Structures for Sampling Rate Conversion.

10. ROUND-OFF EFFECTS IN DIGITAL FILTERS.
Analysis of A/D Quantization Noise. Round-off Effects in IIR Digital Filters. Round-off Effects in FIR Digital Filters.

11. APPLICATIONS IN ADAPTIVE FILTERING.
LMS Algorithm for Coefficient Adjustment. System Identification of System Modeling. Suppression of Narrowband Interference in a Wideband Signal. Adaptive Line Enhancement. Adaptive Channel Equalization.

12. APPLICATIONS IN COMMUNICATIONS
Pulse-Code Modulation. Differential PCM (DPCM). Adaptive PCM and DPCM (ADPCM). Delta Modulation (DM). Linear Predictive Coding (LPC) of Speech. Dual-tone Multifrequency (DTMF) Signals. Binary Digital Communications. Spread-Spectrum Communications.

Title: Digital Signal Processing using MATLAB
Author: John G. Proakis / Vinay K. Ingle
Edition: 3rd Edition
ISBN: 1111427372 | 978-1111427375
Type: eBook
Language: English
Digital Signal Processing
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