


D. SundararajanA Practical Approach to Signals and Systems
€ 110.95
Concisely covers all the important concepts in an easy to understand way Gaining a strong sense of signals and systems fundamentals is key for general proficiency in any electronic engineering discipline, and critical for specialists in signal processing, communication, and control.
Inhoudsopgave: Abbreviations. 1 Introduction. 1.1 The Organization of this Book. 2 Discrete Signals. 2.1 Classification of Signals. 2.1.1 Continuous, Discrete, and Digital Signals. 2.1.2 Periodic and Aperiodic Signals. 2.1.3 Energy and Power Signals. 2.1.4 Even and Odd Symmetric Signals. 2.1.5 Causal and Noncausal Signals. 2.1.6 Deterministic and Random Signals. 2.2 Basic Signals. 2.2.1 Unit Impulse Signal. 2.2.2 Unit Step Signal. 2.2.3 Unit Ramp Signal. 2.2.4 Sinusoids and Exponentials. 2.3 Signal Operations. 2.3.1 Time Shifting. 2.3.2 Time Reversal. 2.3.3 Time Scaling. 2.4 Summary. References. Exercises. 3 Continuous Signals. 3.1 Classification of Signals. 3.1.1 Continuous Signals. 3.1.2 Periodic and Aperiodic Signals. 3.1.3 Energy and Power Signals. 3.1.4 Even and Odd Symmetric Signals. 3.1.5 Causal and Noncausal Signals. 3.2 Basic Signals. 3.2.1 The Unit Step Signal. 3.2.2 The Unit Impulse Signal. 3.2.3 The Unit Ramp Signal. 3.2.4 Sinusoids. 3.3 Signal Operations. 3.3.1 Time Shifting. 3.3.2 Time Reversal. 3.3.3 Time Scaling. 3.4 Summary. Reference. Exercises. 4 Time Domain Analysis of Discrete Systems. 4.1 Difference Equation Model. 4.1.1 System Response. 4.1.2 Impulse Response. 4.1.3 Characterization of Systems by their Responses to Impulse and Unit Step Signals. 4.2 Classification of Systems. 4.2.1 Linear and Nonlinear Systems. 4.2.2 Time Invariant and Time Varying Systems. 4.2.3 Causal and Noncausal Systems. 4.2.4 Instantaneous and Dynamic Systems. 4.2.5 Inverse Systems. 4.2.6 Continuous and Discrete Systems. 4.3 Convolution Summation Model. 4.3.1 Properties of Convolution Summation. 4.3.2 The Difference Equation and the Convolution Summation. 4.3.3 Response to Complex Exponential Input. 4.4 System Stability. 4.5 Realization of Discrete Systems. 4.5.1 Decomposition of Higher Order Systems. 4.5.2 Feedback Systems. 4.6 Summary. References. Exercises. 5 Time Domain Analysis of Continuous Systems. 5.1 Classification of Systems. 5.1.1 Linear and Nonlinear Systems. 5.1.2 Time Invariant and Time Varying Systems. 5.1.3 Causal and Noncausal Systems. 5.1.4 Instantaneous and Dynamic Systems. 5.1.5 Lumped Parameter and Distributed Parameter Systems. 5.1.6 Inverse Systems. 5.2 Difference Equation Model. 5.3 Convolution Integral Model. 5.3.1 Properties of Convolution Integral. 5.4 System Response. 5.4.1 Impulse Response. 5.4.2 Response to Unit Step Input. 5.4.3 Characterization of Systems by their Responses to Impulse and Unit Step Signals. 5.4.4 Response to Complex Exponential Input. 5.5 System Stability. 5.6 Realization of Continuous Systems. 5.6.1 Decomposition of Higher Order Systems. 5.6.2 Feedback Systems. 5.7 Summary. Reference. Exercises. 6 The Discrete Fourier Transform. 6.1 The Time Domain and Frequency Domain. 6.2 The Fourier Analysis. 6.2.1 Versions of Fourier Analysis. 6.3 The Discrete Fourier Transform. 6.3.1 The Approximation of Arbitrary Waveforms with Finite Number Samples. 6.3.2 The DFT and the IDFT. 6.3.3 DFT of Some Basic Signals. 6.4 Properties of the Discrete Fourier Transform. 6.4.1 Linearity. 6.4.2 Periodicity. 6.4.3 Circular Shift of a Sequence. 6.4.4 Circular Shift of a Spectrum. 6.4.5 Symmetry. 6.4.6 Circular Convolution of Time Domain Sequences. 6.4.7 Circular Convolution of Frequency Domain Sequences. 6.4.8 Parseval s Theorem. 6.5 Applications of the Discrete Fourier Transform. 6.5.1 Computation of the Linear Convolution Using the DFT. 6.5.2 Interpolation and Decimation. 6.6. Summary. References. Exercises. 7 Fourier Series. 7.1 Fourier Series. 7.1.1 FS as the Limiting Case of the DFT. 7.1.2 The Compact Trigonometric Form of the FS. 7.1.3 The Trigonometric Form of the FS. 7.1.4 Periodicity of the FS. 7.1.5 Existence of the FS. 7.1.6 Gibbs Phenomenon. 7.2 Properties of the Fourier Series. 7.2.1 Linearity. 7.2.2 Symmetry. 7.2.3 Time Shifting. 7.2.4 Frequency Shifting. 7.2.5 Convolution in the Time Domain. 7.2.6 Convolution in the Frequency Domain. 7.2.7 Duality. 7.2.8 Time Scaling. 7.2.9 Time Differentiation. 7.2.10 Time Integration. 7.2.11 Parseval s Theorem. 7.3 Approximation of the Fourier Series. 7.3.1 Aliasing Effect. 7.4 Applications of the Fourier Series. 7.5 Summary. References. Exercises. 8 The Discrete Time Fourier Transform. 8.1 The Discrete Time Fourier Transform. 8.1.1 The DTFT as the Limiting Case of the DFT. 8.1.2 The Dual Relationship Between the DTFT and the FS. 8.1.3 The DTFT of a Discrete Periodic Signal. 8.1.4 Determination of the DFT from the DTFT. 8.2 Properties of the Discrete Time Fourier Transform. 8.2.1 Linearity. 8.2.2 Time Shifting. 8.2.3 Frequency Shifting. 8.2.4 Convolution in the Time Domain. 8.2.5 Convolution in the Frequency Domain. 8.2.6 Symmetry. 8.2.7 Time Reversal. 8.2.8 Time Expansion. 8.2.9 Frequency Differentiation. 8.2.10 Difference. 8.2.11 Summation. 8.2.12 Parseval s Theorem and the Energy Transfer Function. 8.3 Approximation of the Discrete Time Fourier Transform. 8.3.1 Approximation of the Inverse DTFT by the IDFT. 8.4 Applications of the Discrete Time Fourier Transform. 8.4.1 Transfer Function and the System Response. 8.4.2 Digital Filter Design Using DTFT. 8.4.3 Digital Differentiator. 8.4.4 Hilbert Transform. 8.5 Summary. References. Exercises. 9 The Fourier Transform. 9.1 The Fourier Transform. 9.1.1 The FT as the Limiting Case of the DTFT. 9.1.2 Existence of the FT. 9.2 Properties of the Fourier Transform. 9.2.1 Linearity. 9.2.2 Duality. 9.2.3 Symmetry. 9.2.4 Time Shifting. 9.2.5 Frequency Shifting. 9.2.6 Convolution in the Time Domain. 9.2.7 Convolution in the Frequency Domain. 9.2.8 Conjugation. 9.2.9 Time Reversal. 9.2.10 Time Scaling. 9.2.11 Time Differentiation. 9.2.12 Time Integration. 9.2.13 Frequency Differentiation. 9.2.14 Parseval s Theorem and the Energy Transfer Function. 9.3 Fourier Transform of Mixed Class Signals. 9.3.1 The FT of a Continuous Periodic Signal. 9.3.2 Determination of the FS from the FT. 9.3.3 The FT of a Sampled Signal and the Aliasing Effect. 9.3.4 The FT of a Sampled Aperiodic Signal and the DTFT of the Corresponding Discrete Signal. 9.3.5 The FT of a Sampled Periodic Signal and the DFT of the Corresponding Discrete Signal. 9.3.6 Approximation of the Continuous Signal from its Sampled Version. 9.4 Approximation of the Fourier Transform. 9.5 Applications of the Fourier Transform. 9.5.1 Transfer Function and the System Response. 9.5.2 Ideal Filters and their Unrealizability. 9.5.3 Modulation and Demodulation. 9.6 Summary. References. Exercises. 10 The z Transform. 10.1 Fourier Analysis and the z Transform. 10.2 The z Transform. 10.3 Properties of the z Transform. 10.3.1 Linearity. 10.3.2 Left Shift of a Sequence. 10.3.3 Right Shift of a Sequence. 10.3.4 Convolution. 10.3.5 Multiplication by n. 10.3.6 Multiplication by an. 10.3.7 Summation. 10.3.8 Initial Value. 10.3.9 Final Value. 10.3.10 Transform of Semiperiodic Functions. 10.4 The Inverse z Transform. 10.4.1 Finding the Inverse z Transform. 10.5 Applications of the z Transform. 10.5.1 Transfer Function and the System Response. 10.5.2 Characterization of a System by its Poles and Zeros. 10.5.3 System Stability. 10.5.4 Realization of Systems. 10.5.5 Feedback Systems. 10.6 Summary. References. Exercises. 11 The Laplace Transform. 11.1 The Laplace Transform. 11.1.1 Relationship Between the Laplace Transform and the z Transform. 11.2 Properties of the Laplace Transform. 11.2.1 Linearity. 11.2.2 Time Shifting. 11.2.3 Frequency Shifting. 11.2.4 Time Differentiation. 11.2.5 Integration. 11.2.6 Time Scaling. 11.2.7 Convolution in Time. 11.2.8 Multiplication by t. 11.2.9 Initial Value. 11.2.10 Final Value. 11.2.11 Transform of Semiperiodic Functions. 11.3 The Inverse Laplace Transform. 11.4 Applications of the Laplace Transform. 11.4.1 Transfer Function and the System Response. 11.4.2 Characterization of a System by its Poles and Zeros. 11.4.3 System Stability. 11.4.4 Realization of Systems. 11.4.5 Frequency Domain Representation of Circuits. 11.4.6 Feedback Systems. 11.4.7 Analog Filters. 11.5 Summary. Reference. Exercises. 12 State Space Analysis of Discrete Systems. 12.1 The State Space Model. 12.1.1 Parallel Realization. 12.1.2 Cascade Realization. 12.2 Time Domain Solution of the State Equation. 12.2.1 Iterative Solution. 12.2.2 Closed Form Solution. 12.2.3 The Impulse Response. 12.3 Frequency Domain Solution of the State Equation. 12.4 Linear Transformation of State Vectors. 12.5 Summary. Reference. Exercises. 13 State Space Analysis of Continuous Systems. 13.1 The State Space Model. 13.2 Time Domain Solution of the State Equation. 13.3 Frequency Domain Solution of the State Equation. 13.4 Linear Transformation of State Vectors. 13.5 Summary. Reference. Exercises. Appendix A Transform Pairs and Properties. Appendix B Useful Mathematical Formulas. Answers to Selected Exercises. Index.

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© Copyright 19962018 www.internetboekhandel.nl. Disclaimer Recht van retour 
© Copyright 19962018 www.internetboekhandel.nl. Disclaimer Recht van retour 