This book is intended for use in teaching undergraduate courses on continuous-time and/or discrete-time signals and systems in engineering (and related) disciplines. It provides a detailed introduction to continuous-time and discrete-time signals and systems, with a focus on both theory and applications. The mathematics underlying signals and systems is presented, including topics such as: signal properties, elementary signals, system properties, continuous-time and discrete-time linear time-invariant systems, convolution, continuous-time and discrete-time Fourier series, the continuous-time and discrete-time Fourier transforms, frequency spectra, and the bilateral and unilateral Laplace and z transforms. Applications of the theory are also explored, including: filtering, equalization, amplitude modulation, sampling, feedback control systems, circuit analysis, Laplace-domain techniques for solving differential equations, and z-domain techniques for solving difference equations. Other supplemental material is also included, such as: a detailed introduction to MATLAB, a review of complex analysis, an introduction to partial fraction expansions, an exploration of time-domain techniques for solving differential equations, and information on online video-lecture content for material covered in the book. Throughout the book, many worked-through examples are provided. Problem sets are also provided for each major topic covered.

This document constitutes a detailed set of lecture slides on signals and systems, covering both the continuous-time and discrete-time cases. Some of the topics considered include: signal properties, elementary signals, system properties, linear time-invariant systems, convolution, Fourier series, Fourier transform, Laplace transform, z transform, complex analysis, partial fraction expansions, and MATLAB.

Exploring signals and systems, this work develops continuous-time and discrete-time concepts, highlighting the differences and similarities. Two chapters deal with the Laplace transform and the Z-transform. Basic methods such as filtering, communication an

This document constitutes a detailed set of lecture slides on signals and systems, covering both the continuous-time and discrete-time cases. Some of the topics considered include: signal properties, elementary signals, system properties, linear time-invariant systems, convolution, Fourier series, Fourier transform, Laplace transform, z transform, complex analysis, and partial fraction expansions.

If you understand basic mathematics and know how to program with Python, you’re ready to dive into signal processing. While most resources start with theory to teach this complex subject, this practical book introduces techniques by showing you how they’re applied in the real world. In the first chapter alone, you’ll be able to decompose a sound into its harmonics, modify the harmonics, and generate new sounds. Author Allen Downey explains techniques such as spectral decomposition, filtering, convolution, and the Fast Fourier Transform. This book also provides exercises and code examples to help you understand the material. You’ll explore: Periodic signals and their spectrums Harmonic structure of simple waveforms Chirps and other sounds whose spectrum changes over time Noise signals and natural sources of noise The autocorrelation function for estimating pitch The discrete cosine transform (DCT) for compression The Fast Fourier Transform for spectral analysis Relating operations in time to filters in the frequency domain Linear time-invariant (LTI) system theory Amplitude modulation (AM) used in radio Other books in this series include Think Stats and Think Bayes, also by Allen Downey.

This document constitutes a detailed set of lecture slides on signals and systems, covering both the continuous-time and discrete-time cases. Some of the topics considered include: signal properties, elementary signals, system properties, linear-time invariant systems, convolution, Fourier series, Fourier transform, Laplace transform, z transform, complex analysis, and partial fraction expansions.

This document constitutes a detailed set of lecture slides on signals and systems, covering both the continuous-time and discrete-time cases. Some of the topics considered include: signal properties, elementary signals, system properties, linear-time invariant systems, convolution, Fourier series, Fourier transform, Laplace transform, z transform, complex analysis, and partial fraction expansions.

This book is intended for use in teaching undergraduate courses on continuous-time and/or discrete-time signals and systems in engineering (and related) disciplines. It provides a detailed introduction to continuous-time and discrete-time signals and systems, with a focus on both theory and applications. The mathematics underlying signals and systems is presented, including topics such as: signal properties, elementary signals, system properties, continuous-time and discrete-time linear time-invariant systems, convolution, continuous-time and discrete-time Fourier series, the continuous-time and discrete-time Fourier transforms, frequency spectra, and the bilateral and unilateral Laplace and z transforms. Applications of the theory are also explored, including: filtering, equalization, amplitude modulation, sampling, feedback control systems, circuit analysis, Laplace-domain techniques for solving differential equations, and z-domain techniques for solving difference equations. Other supplemental material is also included, such as: a detailed introduction to MATLAB, a review of complex analysis, an introduction to partial fraction expansions, an exploration of time-domain techniques for solving differential equations, and information on online video-lecture content for material covered in the book. Throughout the book, many worked-through examples are provided. Problem sets are also provided for each major topic covered.

Incorporating new problems and examples, the second edition of Linear Systems and Signals features MATLAB® material in each chapter and at the back of the book. It gives clear descriptions of linear systems and uses mathematics not only to prove axiomatic theory, but also to enhance physical and intuitive understanding.