Introductory course textbook on signals and systems with numerous examples and code snippets implemented in Python
Supported by code examples, Signals and Systems: Theory and Practical Explorations with Python is a textbook resource for a complete introductory course in systems and signals, enabling readers to run Python programs for convolution, discrete time Fourier transforms and series, sampling, and interpolation for a wide range of functions. Readers are guided step-by-step through basic differential equations, basic linear algebra, and calculus to ensure full comprehension of the exercises.
This book is supported by a companion website, hosting interactive material to draw functions, and run programs in Python; it is enriched with audiovisual material via linking to related videos. Links to resources that provide a deeper explanation about the important concepts in the book, such as the systems approach, complex numbers, harmony, the Euler equation, and Hilbert spaces, are also included.
Written by two highly qualified academics, topics covered in Signals and Systems include: - Systems approach for modeling the natural and manmade systems and some application areas - Representation of complex and real signals by basic functions, such as, real and complex exponentials, unit step and unit impulse functions - Properties of signals, such as symmetry, harmony, energy, power, continuity and discreteness - Convolution and correlation operations for continuous time and discrete time signals and systems - Representation of systems by impulse response, frequency response, transfer function, block diagram, differential and difference equations - Properties of systems, such as linearity, time invariance, memory, invertibility, stability and causality - Continuous time and discrete time Fourier analysis in Hilbert space and their extension to Laplaca transform and z-transform - Filtering by Linear Time Invariant systems in time and frequency domains, covering low pass, high pass band pass and band reject filters. - Sampling theorems for continuous time and discrete time systems, covering A/D and D/A conversion, sampling and interpolation.
Signals and Systems is an ideal textbook resource for a one semester introductory course on signals and systems for upper level undergraduate and graduate students in computer science, electrical engineering and data science. It is also a useful reference for professionals working in bioinformatics, robotics, remote sensing, and related fields.
Supported by code examples, Signals and Systems: Theory and Practical Explorations with Python is a textbook resource for a complete introductory course in systems and signals, enabling readers to run Python programs for convolution, discrete time Fourier transforms and series, sampling, and interpolation for a wide range of functions. Readers are guided step-by-step through basic differential equations, basic linear algebra, and calculus to ensure full comprehension of the exercises.
This book is supported by a companion website, hosting interactive material to draw functions, and run programs in Python; it is enriched with audiovisual material via linking to related videos. Links to resources that provide a deeper explanation about the important concepts in the book, such as the systems approach, complex numbers, harmony, the Euler equation, and Hilbert spaces, are also included.
Written by two highly qualified academics, topics covered in Signals and Systems include: - Systems approach for modeling the natural and manmade systems and some application areas - Representation of complex and real signals by basic functions, such as, real and complex exponentials, unit step and unit impulse functions - Properties of signals, such as symmetry, harmony, energy, power, continuity and discreteness - Convolution and correlation operations for continuous time and discrete time signals and systems - Representation of systems by impulse response, frequency response, transfer function, block diagram, differential and difference equations - Properties of systems, such as linearity, time invariance, memory, invertibility, stability and causality - Continuous time and discrete time Fourier analysis in Hilbert space and their extension to Laplaca transform and z-transform - Filtering by Linear Time Invariant systems in time and frequency domains, covering low pass, high pass band pass and band reject filters. - Sampling theorems for continuous time and discrete time systems, covering A/D and D/A conversion, sampling and interpolation.
Signals and Systems is an ideal textbook resource for a one semester introductory course on signals and systems for upper level undergraduate and graduate students in computer science, electrical engineering and data science. It is also a useful reference for professionals working in bioinformatics, robotics, remote sensing, and related fields.
