
This comprehensive exploration of signals and systems develops continuous-time
and discrete-time concepts/methods in parallel -- highlighting
the similarities and differences -- and features introductory treatments
of the applications of these basic methods in such areas as filtering,
communication, sampling, discrete-time processing of continuous-time
signals, and feedback. Relatively self-contained, the text assumes
no prior experience with system analysis, convolution, Fourier analysis,
or Laplace and z-transforms.

Develops continuous-time and discrete-time concepts in
parallel -- highlighting the similarities and differences. E.g.:
- Ch. 1 on basic signals and system properties, Ch. 2 on
linear time-invariant systems, and Ch. 3 on Fourier series representation
each develop the continuous-time and discrete-time concepts in parallel.
- Ch. 9 on the Laplace Transform and Ch. 10 on the Z-transform
deal with the two domains separately, but often draw parallels between
results in the two domains.
Introduces some of the important uses of the basic methods
that are developed -- e.g., filtering, communication, sampling, discrete-time
processing of continuous-time signals, and feedback.
Includes an up-to-date bibliography.
NEW--A companion book contains MATLAB-based
computer exercises for each topic in the text.
NEW--Material on Fourier analysis has been reorganized
significantly to provide an easier path for the student to master
and appreciate the importance of this topic. Now represented in four
chapters, each of which is far more streamlined and focused, introducing
a smaller and more cohesive set of topics. This will greatly enhance
the students ability to organize their understanding of the material.
NEW--Frequency-domain filtering is introduced very
early in the development to provide a central and concrete illustration
of why this topic is important and to provide some intuition with
a minimal amount of mathematical preliminaries. The students will
be able to see why this topic is so important and gain some intuition
which will enhance his or her appreciation of the developments that
follow.
NEW--Much of the advanced material that had appeared
in the Fourier transform chapters in the first edition have now been
pulled together into the time and frequency domain chapter, so that
only the basic concepts are introduced in these chapters; and provide
a more cohesive treatment of time and frequency domain issues.
NEW--Relocates coverage of Sampling before Communication.
- Allows instructor and students to discuss important forms
of communication, namely those involving discrete or digital signals,
in which sampling concepts are intimately involved.
NEW--Includes significantly more worked examples.
NEW--Provides over 600 chapter-end problems, -- 20
per chapter, with answers (not solutions).
NEW--Features a majority of new chapter-end problems.
NEW--Chapter-end Problems have been reorganized
and assembled to aid the student and instructor. They provide a better
balance between exercises developing basic skills and understanding
ones that pursue more advanced problem-solving skills. New edition
organizes chapter-end problems into four types of sections which makes
it easier for the instructor and student to locate the problems that
will best serve their purposes; and provides two types of basic problems,
ones with answers (but not solutions); and ones with solutions to
provide immediate feedback to the student while attempting to master
the material. The four types of chapter-end problems are--
- Basic Problems with Answers.
- Basic Problems.
- Advanced Problems.
- Extension Problems.

(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.
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