The book provides a balanced and integrated treatment of continuous–time and discrete–time forms of signals and systems intended to reflect their roles in engineering practice. This approach has the pedagogical advantage of helping the reader see the fundamental similarities and differences between discrete–time and continuous–time representations.

Chapter 1. Introduction. Chapter 2. Time-Domain Representations of Linear Time-Invariant Systems. Chapter 3. Fourier Representations of Signals and Linear Time Invariant Systems. Chapter 4. Applications of Fourier Representations to Mixed Signal Classes. Chapter 5. Application to Communication Systems. Chapter 6. Representing Signals by Using Continuous-Time Complex Exponentials: The Laplace Transform. Chapter 7. Representing Signals by Using Discrete-Time Complex Exponentials: The z-Transform. Chapter 8. Application to Filters and Equalizers. Chapter 9. Application to Linear Feedback Systems. Chapter 10. Epilogue. Appendix A: Selected Mathematical Identities. Appendix B: Partial-Fraction Expansions. Appendix C: Tables of Fourier Representations and Properties. Appendix D: Tables of Laplace Transforms and Properties. Appendix E: Tables of z-Transforms and Properties. Appendix F: Introduction to MATLAB. Index.

Reaching the conceptual peaks of signals and systems can be a challenge. But well-known authors Simon Haykin and Barry Van Veen help you clearly see connections among concepts and recognize the relevance of signals and systems to the broader field of electrical engineering. Features New problems: The new edition includes opportunities for demonstration and practice throughout.New themed examples: Six new themed examples demonstrate the range of problems to which signal and system concepts can be applied, including RC circuits, MEMS accelerometer, radar range measurement, moving average system, multipath communication channel, and first order recursive discrete time computation. The authors revisit these themed examples using different mathematical tools to show how each tool give unique insight into the problem at hand in the context of a real world problem.New coverage throughout: Contains new sections on MEMS and derivatives of the unit-impulse function, the Costas receiver for demodulation of double sideband-suppressed carrier-modulated signals, and the fundamental notion of feedback and 'why feedback', as well as more detailed treatment of wavelets and the stability of nonlinear feedback systems. A new section on noise has also been added to Chapter 1. Chapter 4 now focuses exclusively on building bridges between the four basic Fourier representation for applications in which there is a missing of signal classes.Many opportunities for practice: All examples are based on real-world problems and emphasize the correct mathematical steps needed for applying the theory. Problems vary from drill-based to complex, so you'll have plenty of room to practice.Integrated, flexible coverage of MATLAB: MATLAB techniques and uses, as well as MATLAB practice problems, and provided at the end of each chapter.

Introduction Time-Domain Representations for Linear Time-Invariant Systems Fourier Representations for Signals and Linear Time-Invariant Systems Applications of Fourier Representations and Mixed Signal Classes Application to Communication Systems Representation of Signals Using Continuous-Time Complex Exponentials: The Laplace Transform Representation of Signals Using Discrete-Time Complex Exponentials: the z-Transform Application to Filters And Equalizers Application to Feedback Systems Epilogue Appendices Selected Mathematical Identities Partial Fraction Expansions Tables of Fourier Representations and Properties Tables of Laplace Transforms and Properties Tables of z-Transforms and Properties Introduction to Matlab