1. Discrete-time signal processing [2010]
- Book
- xxviii, 1108 p. : ill. ; 25 cm.
- Previous edition TOC 1. Introduction. 2. Discrete-Time Signals and Systems. Introduction. Discrete-time Signals: Sequences. Discrete-time Systems. Linear Time-Invariant Systems. Properties of Linear Time-Invariant Systems. Linear Constant-Coefficient Difference Equations. Frequency-Domain Representation of Discrete-Time Signals and Systems. Representation of Sequence by Fourier Transforms. Symmetry Properties of the Fourier Transform. Fourier Transform Theorems. Discrete-Time Random Signals. Summary. 3. The z-Transform. Introduction. The z-Transform. Properties of the Region of Convergence for the z-Transform. The Inverse z-Transform. z-Transform Properties. Summary. 4. Sampling of Continuous-Time Signals. Introduction. Periodic Sampling. Frequency-Domain Representation of Sampling. Reconstruction of a Bandlimited Signal from its Samples. Discrete-Time Processing of Continuous-Time Signals. Continuous-Time Processing of Discrete-Time Signals. Changing the Sampling Rate Using Discrete-Time Processing. Practical Considerations. Oversampling and Noise Shaping. Summary. 5. Transform Analysis of Linear Time-Invariant Systems. Introduction. The Frequency Response of LTI Systems. System Functions for Systems Characterized by Linea. Frequency Response for Rational System Functions. Relationship Between Magnitude and Phase. All-Pass Systems. Minimum-Phase Systems. Linear Systems with Generalized Linear Phase. Summary. 6. Structures for Discrete-Time Systems. Introduction. Block Diagram Representation of Linear Constant-Coefficient Difference Equations. Signal Flow Graph Representation of Linear Constant-Coefficient Difference Equations. Basic Structures for IIR Systems. Transposed Forms. Basic Network Structures for FIR Systems. Overview of Finite-Precision Numerical Effects. The Effects of Coefficient Quantization. Effects of Roundoff Noise in Digital Filters. Zero-Input Limit Cycles in Fixed-Point Realizations of IIR Digital Filters. Summary. 7. Filter Design Techniques. Introduction. Design of Discrete-Time IIR Filters from Continuous-Time Filters. Design of FIR Filters by Windowing. Examples of FIR Filter Design by the Kaiser Window Method. Optimum Approximations of FIR Filters. Examples of FIR Equiripple Approximation. Comments on IIR and FIR Digital Filters. Summary. 8. The Discrete Fourier Transform. Introduction. Representation of Periodic Sequences: the Discrete Fourier Series. Summary of Properties of the DFS Representation of Periodic Sequences. The Fourier Transform of Periodic Signals. Sampling the Fourier Transform. Fourier Representation of Finite-Duration Sequences: The Discrete-Fourier Transform. Properties of the Discrete Fourier Transform. Summary of Properties of the Discrete Fourier Transform. Linear Convolution Using the Discrete Fourier Transform. The Discrete Cosine Transform (DCT). Summary. 9. Computation of the Discrete Fourier Transform. Introduction. Efficient Computation of the Discrete Fourier Transform. The Goertzel Algorithm Decimation-in-Time FFT Algorithms. Decimation-in-Frequency FFT Algorithms. Practical Considerations Implementation of the DFT Using Convolution. Summary. 10. Fourier Analysis of Signals Using the Discrete Fourier Transform. Introduction. Fourier Analysis of Signals Using the DFT. DFT Analysis of Sinusoidal Signals. The Time-Dependent Fourier Transform. Block Convolution Using the Time-Dependent Fourier Transform. Fourier Analysis of Nonstationary Signals. Fourier Analysis of Stationary Random Signals: the Periodogram. Spectrum Analysis of Random Signals Using Estimates of the Autocorrelation Sequence. Summary. 11. Discrete Hilbert Transforms. Introduction. Real and Imaginary Part Sufficiency of the Fourier Transform for Causal Sequences. Sufficiency Theorems for Finite-Length Sequences. Relationships Between Magnitude and Phase. Hilbert Transform Relations for Complex Sequences. Summary. Appendix A: Random Signals. Discrete-Time Random Process. Averages. Properties of Correlation and Covariance Sequences. Transform Representation of Random Signals. Appendix B: Continuous-Time Filters. Butterworth Lowpass Filters. Chebyshev Filters. Elliptic Filters.
- (source: Nielsen Book Data)9780131988422 20160606
(source: Nielsen Book Data)9780131988422 20160606
- Previous edition TOC 1. Introduction. 2. Discrete-Time Signals and Systems. Introduction. Discrete-time Signals: Sequences. Discrete-time Systems. Linear Time-Invariant Systems. Properties of Linear Time-Invariant Systems. Linear Constant-Coefficient Difference Equations. Frequency-Domain Representation of Discrete-Time Signals and Systems. Representation of Sequence by Fourier Transforms. Symmetry Properties of the Fourier Transform. Fourier Transform Theorems. Discrete-Time Random Signals. Summary. 3. The z-Transform. Introduction. The z-Transform. Properties of the Region of Convergence for the z-Transform. The Inverse z-Transform. z-Transform Properties. Summary. 4. Sampling of Continuous-Time Signals. Introduction. Periodic Sampling. Frequency-Domain Representation of Sampling. Reconstruction of a Bandlimited Signal from its Samples. Discrete-Time Processing of Continuous-Time Signals. Continuous-Time Processing of Discrete-Time Signals. Changing the Sampling Rate Using Discrete-Time Processing. Practical Considerations. Oversampling and Noise Shaping. Summary. 5. Transform Analysis of Linear Time-Invariant Systems. Introduction. The Frequency Response of LTI Systems. System Functions for Systems Characterized by Linea. Frequency Response for Rational System Functions. Relationship Between Magnitude and Phase. All-Pass Systems. Minimum-Phase Systems. Linear Systems with Generalized Linear Phase. Summary. 6. Structures for Discrete-Time Systems. Introduction. Block Diagram Representation of Linear Constant-Coefficient Difference Equations. Signal Flow Graph Representation of Linear Constant-Coefficient Difference Equations. Basic Structures for IIR Systems. Transposed Forms. Basic Network Structures for FIR Systems. Overview of Finite-Precision Numerical Effects. The Effects of Coefficient Quantization. Effects of Roundoff Noise in Digital Filters. Zero-Input Limit Cycles in Fixed-Point Realizations of IIR Digital Filters. Summary. 7. Filter Design Techniques. Introduction. Design of Discrete-Time IIR Filters from Continuous-Time Filters. Design of FIR Filters by Windowing. Examples of FIR Filter Design by the Kaiser Window Method. Optimum Approximations of FIR Filters. Examples of FIR Equiripple Approximation. Comments on IIR and FIR Digital Filters. Summary. 8. The Discrete Fourier Transform. Introduction. Representation of Periodic Sequences: the Discrete Fourier Series. Summary of Properties of the DFS Representation of Periodic Sequences. The Fourier Transform of Periodic Signals. Sampling the Fourier Transform. Fourier Representation of Finite-Duration Sequences: The Discrete-Fourier Transform. Properties of the Discrete Fourier Transform. Summary of Properties of the Discrete Fourier Transform. Linear Convolution Using the Discrete Fourier Transform. The Discrete Cosine Transform (DCT). Summary. 9. Computation of the Discrete Fourier Transform. Introduction. Efficient Computation of the Discrete Fourier Transform. The Goertzel Algorithm Decimation-in-Time FFT Algorithms. Decimation-in-Frequency FFT Algorithms. Practical Considerations Implementation of the DFT Using Convolution. Summary. 10. Fourier Analysis of Signals Using the Discrete Fourier Transform. Introduction. Fourier Analysis of Signals Using the DFT. DFT Analysis of Sinusoidal Signals. The Time-Dependent Fourier Transform. Block Convolution Using the Time-Dependent Fourier Transform. Fourier Analysis of Nonstationary Signals. Fourier Analysis of Stationary Random Signals: the Periodogram. Spectrum Analysis of Random Signals Using Estimates of the Autocorrelation Sequence. Summary. 11. Discrete Hilbert Transforms. Introduction. Real and Imaginary Part Sufficiency of the Fourier Transform for Causal Sequences. Sufficiency Theorems for Finite-Length Sequences. Relationships Between Magnitude and Phase. Hilbert Transform Relations for Complex Sequences. Summary. Appendix A: Random Signals. Discrete-Time Random Process. Averages. Properties of Correlation and Covariance Sequences. Transform Representation of Random Signals. Appendix B: Continuous-Time Filters. Butterworth Lowpass Filters. Chebyshev Filters. Elliptic Filters.
- (source: Nielsen Book Data)9780131988422 20160606
(source: Nielsen Book Data)9780131988422 20160606
Engineering Library (Terman)
Engineering Library (Terman) | Status |
---|---|
On reserve: Ask at circulation desk | |
TK5102.5 .O2452 2010 | Unknown 4-hour loan |
TK5102.5 .O2452 2010 | Unknown 4-hour loan |
EE-102B-01
- Course
- EE-102B-01 -- Signal Processing and Linear Systems II
- Instructor(s)
- Kahn, Joseph M.
2. Signals & systems [1997]
- Book
- xxx, 957 p. : ill. ; 25 cm.
- (NOTE: Each chapter begins with an Introduction and concludes with a Summary.) 1. Signals and Systems. Continuous-Time and Discrete-Time Signals. Transformations of the Independent Variable. Exponential and Sinusoidal Signals. The Unit Impulse and Unit Step Functions. Continuous-Time and Discrete-Time Systems. Basic System Properties. 2. Linear Time-Invariant Systems. Discrete-Time LTI Systems: The Convolution Sum. Continuous-Time LTI Systems: The Convolution Integral. Properties of Linear Time-Invariant Systems. Causal LTI Systems Described by Differential and Difference Equations. Singularity Functions. 3. Fourier Series Representation of Periodic Signals. A Historical Perspective. The Response of LTI Systems to Complex Exponentials. Fourier Series Representation of Continuous-Time Periodic Signals. Convergence of the Fourier Series. Properties of Continuous-Time Fourier Series. Fourier Series Representation of Discrete-Time Periodic Signals. Properties of Discrete-Time Fourier Series. Fourier Series and LTI Systems. Filtering. Examples of Continuous-Time Filters Described by Differential Equations. Examples of Discrete-Time Filters Described by Difference Equations. 4. The Continuous-Time Fourier Transform. Representation of Aperiodic Signals: The Continuous-Time Fourier Transform. The Fourier Transform for Periodic Signals. Properties of the Continuous-Time Fourier Transform. The Convolution Property. The Multiplication Property. Tables of Fourier Properties and Basic Fourier Transform Pairs. Systems Characterized by Linear Constant-Coefficient Differential Equations. 5. The Discrete-Time Fourier Transform. Representation of Aperiodic Signals: The Discrete-Time Fourier Transform. The Fourier Transform for Periodic Signals. Properties of the Discrete-Time Fourier Transform. The Convolution Property. The Multiplication Property. Tables of Fourier Transform Properties and Basic Fourier Transform Pairs. Duality. Systems Characterized by Linear Constant-Coefficient Difference Equations. 6. Time- and Frequency Characterization of Signals and Systems. The Magnitude-Phase Representation of the Fourier Transform. The Magnitude-Phase Representation of the Frequency Response of LTI Systems. Time-Domain Properties of Ideal Frequency-Selective Filters. Time- Domain and Frequency-Domain Aspects of Nonideal Filters. First-Order and Second-Order Continuous-Time Systems. First-Order and Second-Order Discrete-Time Systems. Examples of Time- and Frequency-Domain Analysis of Systems. 7. Sampling. Representation of a Continuous-Time Signal by Its Samples: The Sampling Theorem. Reconstruction of a Signal from Its Samples Using Interpolation. The Effect of Undersampling: Aliasing. Discrete-Time Processing of Continuous-Time Signals. Sampling of Discrete-Time Signals. 8. Communication Systems. Complex Exponential and Sinusoidal Amplitude Modulation. Demodulation for Sinusoidal AM. Frequency-Division Multiplexing. Single-Sideband Sinusoidal Amplitude Modulation. Amplitude Modulation with a Pulse-Train Carrier. Pulse-Amplitude Modulation. Sinusoidal Frequency Modulation. Discrete-Time Modulation. 9. The Laplace Transform. The Laplace Transform. The Region of Convergence for Laplace Transforms. The Inverse Laplace Transform. Geometric Evaluation of the Fourier Transform from the Pole-Zero Plot. Properties of the Laplace Transform. Some Laplace Transform Pairs. Analysis and Characterization of LTI Systems Using the Laplace Transform. System Function Algebra and Block Diagram Representations. The Unilateral Laplace Transform. 10. The Z-Transform. The z-Transform. The Region of Convergence for the z-Transform. The Inverse z-Transform. Geometric Evaluation of the Fourier Transform from the Pole-Zero Plot. Properties of the z-Transform. Some Common z-Transform Pairs. Analysis and Characterization of LTI Systems Using z-Transforms. System Function Algebra and Block Diagram Representations. The Unilateral z-Transforms. 11. Linear Feedback Systems. Linear Feedback Systems. Some Applications and Consequences of Feedback. Root-Locus Analysis of Linear Feedback Systems. The Nyquist Stability Criterion. Gain and Phase Margins. Appendix: Partial-Fraction Expansion. Bibliography. Answers. Index.
- (source: Nielsen Book Data)9780138147570 20160528
(source: Nielsen Book Data)9780138147570 20160528
- (NOTE: Each chapter begins with an Introduction and concludes with a Summary.) 1. Signals and Systems. Continuous-Time and Discrete-Time Signals. Transformations of the Independent Variable. Exponential and Sinusoidal Signals. The Unit Impulse and Unit Step Functions. Continuous-Time and Discrete-Time Systems. Basic System Properties. 2. Linear Time-Invariant Systems. Discrete-Time LTI Systems: The Convolution Sum. Continuous-Time LTI Systems: The Convolution Integral. Properties of Linear Time-Invariant Systems. Causal LTI Systems Described by Differential and Difference Equations. Singularity Functions. 3. Fourier Series Representation of Periodic Signals. A Historical Perspective. The Response of LTI Systems to Complex Exponentials. Fourier Series Representation of Continuous-Time Periodic Signals. Convergence of the Fourier Series. Properties of Continuous-Time Fourier Series. Fourier Series Representation of Discrete-Time Periodic Signals. Properties of Discrete-Time Fourier Series. Fourier Series and LTI Systems. Filtering. Examples of Continuous-Time Filters Described by Differential Equations. Examples of Discrete-Time Filters Described by Difference Equations. 4. The Continuous-Time Fourier Transform. Representation of Aperiodic Signals: The Continuous-Time Fourier Transform. The Fourier Transform for Periodic Signals. Properties of the Continuous-Time Fourier Transform. The Convolution Property. The Multiplication Property. Tables of Fourier Properties and Basic Fourier Transform Pairs. Systems Characterized by Linear Constant-Coefficient Differential Equations. 5. The Discrete-Time Fourier Transform. Representation of Aperiodic Signals: The Discrete-Time Fourier Transform. The Fourier Transform for Periodic Signals. Properties of the Discrete-Time Fourier Transform. The Convolution Property. The Multiplication Property. Tables of Fourier Transform Properties and Basic Fourier Transform Pairs. Duality. Systems Characterized by Linear Constant-Coefficient Difference Equations. 6. Time- and Frequency Characterization of Signals and Systems. The Magnitude-Phase Representation of the Fourier Transform. The Magnitude-Phase Representation of the Frequency Response of LTI Systems. Time-Domain Properties of Ideal Frequency-Selective Filters. Time- Domain and Frequency-Domain Aspects of Nonideal Filters. First-Order and Second-Order Continuous-Time Systems. First-Order and Second-Order Discrete-Time Systems. Examples of Time- and Frequency-Domain Analysis of Systems. 7. Sampling. Representation of a Continuous-Time Signal by Its Samples: The Sampling Theorem. Reconstruction of a Signal from Its Samples Using Interpolation. The Effect of Undersampling: Aliasing. Discrete-Time Processing of Continuous-Time Signals. Sampling of Discrete-Time Signals. 8. Communication Systems. Complex Exponential and Sinusoidal Amplitude Modulation. Demodulation for Sinusoidal AM. Frequency-Division Multiplexing. Single-Sideband Sinusoidal Amplitude Modulation. Amplitude Modulation with a Pulse-Train Carrier. Pulse-Amplitude Modulation. Sinusoidal Frequency Modulation. Discrete-Time Modulation. 9. The Laplace Transform. The Laplace Transform. The Region of Convergence for Laplace Transforms. The Inverse Laplace Transform. Geometric Evaluation of the Fourier Transform from the Pole-Zero Plot. Properties of the Laplace Transform. Some Laplace Transform Pairs. Analysis and Characterization of LTI Systems Using the Laplace Transform. System Function Algebra and Block Diagram Representations. The Unilateral Laplace Transform. 10. The Z-Transform. The z-Transform. The Region of Convergence for the z-Transform. The Inverse z-Transform. Geometric Evaluation of the Fourier Transform from the Pole-Zero Plot. Properties of the z-Transform. Some Common z-Transform Pairs. Analysis and Characterization of LTI Systems Using z-Transforms. System Function Algebra and Block Diagram Representations. The Unilateral z-Transforms. 11. Linear Feedback Systems. Linear Feedback Systems. Some Applications and Consequences of Feedback. Root-Locus Analysis of Linear Feedback Systems. The Nyquist Stability Criterion. Gain and Phase Margins. Appendix: Partial-Fraction Expansion. Bibliography. Answers. Index.
- (source: Nielsen Book Data)9780138147570 20160528
(source: Nielsen Book Data)9780138147570 20160528
Engineering Library (Terman)
Engineering Library (Terman) | Status |
---|---|
On reserve: Ask at circulation desk | |
QA402 .O63 1997 | Unknown 4-hour loan |
QA402 .O63 1997 | In-library use 4-hour loan |
QA402 .O63 1997 | Unknown 4-hour loan |
Stacks | |
QA402 .O63 1997 | Unavailable Missing Request |
QA402 .O63 1997 | Unavailable Missing Request |
EE-102B-01
- Course
- EE-102B-01 -- Signal Processing and Linear Systems II
- Instructor(s)
- Kahn, Joseph M.