| Preface and Acknowledgments | |
| An Introduction to Signal Processing | |
| Some Signal Processing History | |
| The Signal Processing System | |
| Describing Signals | |
| Representation of Signals | |
| Classification of Signals | |
| Mathematical Description of Specific Signals | |
| Continuous-Time Systems and Discrete-Time Systems | |
| The Frequency Domain of Digital Signals and Systems | |
| The Discrete-Time Fourier Transform | |
| Example Calculations with the Discrete-Time Fourier Transform | |
| Effects of Signal Length and Windowing on the Discrete-Time Fourier Transform | |
| The Discrete Fourier Transform | |
| Inverse Transforms | |
| Signal Power in the Time a...nd Frequency Domains | |
| Random Noise in Signals | |
| The Frequency Response of a Linear Time-Invariant DSP System | |
| Finite Impulse Response Filter Design | |
| General Concepts of FIR Filter Design | |
| Phase Distortion and Linear Phase | |
| The Ideal Window Design Method | |
| Sampling Design of FIR Filters | |
| Optimal FIR Design Methods in MATLAB | |
| Infinite Impulse Response Filter Design | |
| The General Concepts of IIR Filter Design | |
| Design by Pole-Zero Location | |
| Digital Realization of Classical Analog Filters | |
| MATLAB IIR Design Tools | |
| Coefficient Quantization with IIR Filters | |
| Over-Sampling and Multi-Rate DSP Systems | |
| Digital Anti-Aliasing | |
| Down-sampling and Decimation | |
| Up-Sampling and Interpolation | |
| Sampling Rate Conversion by Rational Factors | |
| Over-Sampling and Noise | |
| Delta-Sigma Quantization | |
| Correlation and Auto-correlation of Signals | |
| The Cross-Correlation of Signals | |
| Auto-correlation | |
| Using Auto-correlation to Detect Signals in Noise | |
| Detecting and Ranging a Return Echo Contaminated with Noise | |
| Adaptive Filters | |
| Theory of Adaptive Filters | |
| The Adaptive Predictor | |
| Adaptive System Identification | |
| Basic Digital Signal Processing of Images | |
| The Structure of Digital Images | |
| Image Sampling, Quantization, and Aliasing | |
| Arithmetic Operations on Image Matrices | |
| Statistical Properties and Enhancement of Images | |
| Image Filtering | |
| Discrete Fourier Transform of Images | |
| Case Study: JPEG Compression of Images | |
| Wavelets | |
| Non-Stationary Signals | |
| Sub-Band Decomposition and Reconstruction of Signals | |
| Analysis of Signals Using Wavelets | |
| Signal Compression Using Wavelets | |
| Computational Case Studies | |
| Dual-Tone Multi-Frequency Signaling | |
| Pattern Recognition in Images | |
| Speech Processing: Compression and Synthesis | |
| Echo Cancellation with Adaptive Filters | |
| Wavelet De-Noising and Compression of Images | |
| Other Case Studies Appendices | |
| Complex Numbers | |
| Imaginary Numbers | |
| Why We Need Imaginary Numbers | |
| Complex Numbers | |
| Polar Form of a Complex Number and Euler?s Equation | |
| Magnitude and Angle of a Complex Number | |
| Complex Conjugate | |
| Complex Exponential Forms of the Sine and Cosine Functions | |
| Complex Functions | |
| Working With Complex Numbers | |
| A-to-D and D-to-A Conversion Methods | |
| What Makes a DSP a DSP? | |
| Mathematical Detail and Proofs | |
| Fourier Analysis | |
| The inverse DTFT | |
| The inverse DFT | |
| Statistical properties of digital signals: mean, variance, covariance, and expectation | |
| The least-mean-squares algorithm to find the minimum of a function | |
| Table of Contents provided by Publisher. All Rights Reserved. |
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