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A typical undergraduate electrical engineering curriculum incorporates a signals and systems course. The widely used approach for the laboratory component of such courses involves the utilization of MATLAB to implement signals and systems concepts. This book presents a newly developed laboratory paradigm where MATLAB codes are made to run on smartphones which are possessed by nearly all students. As a result, this laboratory paradigm provides an anywhere-anytime hardware platform or processing board for students to learn implementation aspects of signals and systems concepts. The book covers the laboratory experiments that are normally covered in signals and systems courses and discusses how to run MATLAB codes for these experiments as apps on both Android and iOS smartphones, thus enabling a truly mobile laboratory paradigm.
Book Synopsis Anywhere-Anytime Signals and Systems Laboratory by : Nasser Kehtarnavaz
Download or read book Anywhere-Anytime Signals and Systems Laboratory written by Nasser Kehtarnavaz and published by Morgan & Claypool Publishers. This book was released on 2020-07-09 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: A typical undergraduate electrical engineering curriculum incorporates a signals and systems course. The widely used approach for the laboratory component of such courses involves the utilization of MATLAB to implement signals and systems concepts. This book presents a newly developed laboratory paradigm where MATLAB codes are made to run on smartphones which are possessed by nearly all students. As a result, this laboratory paradigm provides an anywhere-anytime hardware platform or processing board for students to learn implementation aspects of signals and systems concepts. The book covers the laboratory experiments that are normally covered in signals and systems courses and discusses how to run MATLAB codes for these experiments as apps on both Android and iOS smartphones, thus enabling a truly mobile laboratory paradigm.
A typical undergraduate electrical engineering curriculum incorporates a signals and systems course. The widely used approach for the laboratory component of such courses involves the utilization of MATLAB to implement signals and systems concepts. This lecture series book presents a newly developed laboratory paradigm where MATLAB codes are made to run on smartphones, which most students already possess. This smartphone-based approach enables an anywhere-anytime platform for students to conduct signals and systems experiments. This book covers the laboratory experiments that are normally covered in signals and systems courses and discusses how to run MATLAB codes for these experiments on both Android and iOS smartphones, thus enabling a truly mobile laboratory environment for students to learn the implementation aspects of signals and systems concepts. A zipped file of the codes discussed in the book can be acquired via the website.
Book Synopsis Anywhere-Anytime Signals and Systems Laboratory by : Nasser Kehtarnavaz
Download or read book Anywhere-Anytime Signals and Systems Laboratory written by Nasser Kehtarnavaz and published by Springer Nature. This book was released on 2018-11-06 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: A typical undergraduate electrical engineering curriculum incorporates a signals and systems course. The widely used approach for the laboratory component of such courses involves the utilization of MATLAB to implement signals and systems concepts. This lecture series book presents a newly developed laboratory paradigm where MATLAB codes are made to run on smartphones, which most students already possess. This smartphone-based approach enables an anywhere-anytime platform for students to conduct signals and systems experiments. This book covers the laboratory experiments that are normally covered in signals and systems courses and discusses how to run MATLAB codes for these experiments on both Android and iOS smartphones, thus enabling a truly mobile laboratory environment for students to learn the implementation aspects of signals and systems concepts. A zipped file of the codes discussed in the book can be acquired via the website.
A typical undergraduate electrical engineering curriculum incorporates a signals and systems course. The widely used approach for the laboratory component of such courses involves the utilization of MATLAB to implement signals and systems concepts. This book presents a newly developed laboratory paradigm where MATLAB codes are made to run on smartphones, which most students already possess. This smartphone-based approach enables an anywhere-anytime platform for students to conduct signals and systems experiments. This book covers the laboratory experiments that are normally covered in signals and systems courses and discusses how to run MATLAB codes for these experiments on smartphones, thus enabling a truly mobile laboratory environment for students to learn the implementation aspects of signals and systems concepts. A zipped file of the codes discussed in the book can be acquired via the website http://sites.fastspring.com/bookcodes/product/SignalsSystemsBookcodes.
Book Synopsis Anywhere-Anytime Signals and Systems Laboratory by : Nasser Kehtarnavaz
Download or read book Anywhere-Anytime Signals and Systems Laboratory written by Nasser Kehtarnavaz and published by Springer Nature. This book was released on 2016-10-17 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: A typical undergraduate electrical engineering curriculum incorporates a signals and systems course. The widely used approach for the laboratory component of such courses involves the utilization of MATLAB to implement signals and systems concepts. This book presents a newly developed laboratory paradigm where MATLAB codes are made to run on smartphones, which most students already possess. This smartphone-based approach enables an anywhere-anytime platform for students to conduct signals and systems experiments. This book covers the laboratory experiments that are normally covered in signals and systems courses and discusses how to run MATLAB codes for these experiments on smartphones, thus enabling a truly mobile laboratory environment for students to learn the implementation aspects of signals and systems concepts. A zipped file of the codes discussed in the book can be acquired via the website http://sites.fastspring.com/bookcodes/product/SignalsSystemsBookcodes.
A typical undergraduate electrical engineering curriculum incorporates a signals and systems course. The widely used approach for the laboratory component of such courses involves the utilization of MATLAB to implement signals and systems concepts. This lecture series book presents a newly developed laboratory paradigm where MATLAB codes are made to run on smartphones, which most students already possess. This smartphone-based approach enables an anywhere-anytime platform for students to conduct signals and systems experiments. This book covers the laboratory experiments that are normally covered in signals and systems courses and discusses how to run MATLAB codes for these experiments on both Android and iOS smartphones, thus enabling a truly mobile laboratory environment for students to learn the implementation aspects of signals and systems concepts. A zipped file of the codes discussed in the book can be acquired via the website.
Book Synopsis Anywhere-Anytime Signals and Systems Laboratory by : Nasser Kehtarnavaz
Download or read book Anywhere-Anytime Signals and Systems Laboratory written by Nasser Kehtarnavaz and published by Morgan & Claypool. This book was released on 2018-11-06 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: A typical undergraduate electrical engineering curriculum incorporates a signals and systems course. The widely used approach for the laboratory component of such courses involves the utilization of MATLAB to implement signals and systems concepts. This lecture series book presents a newly developed laboratory paradigm where MATLAB codes are made to run on smartphones, which most students already possess. This smartphone-based approach enables an anywhere-anytime platform for students to conduct signals and systems experiments. This book covers the laboratory experiments that are normally covered in signals and systems courses and discusses how to run MATLAB codes for these experiments on both Android and iOS smartphones, thus enabling a truly mobile laboratory environment for students to learn the implementation aspects of signals and systems concepts. A zipped file of the codes discussed in the book can be acquired via the website.
A typical undergraduate electrical engineering curriculum incorporates a signals and systems course. The widely used approach for the laboratory component of such courses involves the utilization of MATLAB to implement signals and systems concepts. This book presents a newly developed laboratory paradigm where MATLAB codes are made to run on smartphones which are possessed by nearly all students. As a result, this laboratory paradigm provides an anywhere-anytime hardware platform or processing board for students to learn implementation aspects of signals and systems concepts. The book covers the laboratory experiments that are normally covered in signals and systems courses and discusses how to run MATLAB codes for these experiments as apps on both Android and iOS smartphones, thus enabling a truly mobile laboratory paradigm. A zipped file of the codes discussed in the book can be acquired via the website http://sites.fastspring.com/bookcodes/product/SignalsSystemsBookcodesThirdEdition
Book Synopsis Anywhere-Anytime Signals and Systems Laboratory by : Fatemeh Saki
Download or read book Anywhere-Anytime Signals and Systems Laboratory written by Fatemeh Saki and published by Springer Nature. This book was released on 2022-05-31 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: A typical undergraduate electrical engineering curriculum incorporates a signals and systems course. The widely used approach for the laboratory component of such courses involves the utilization of MATLAB to implement signals and systems concepts. This book presents a newly developed laboratory paradigm where MATLAB codes are made to run on smartphones which are possessed by nearly all students. As a result, this laboratory paradigm provides an anywhere-anytime hardware platform or processing board for students to learn implementation aspects of signals and systems concepts. The book covers the laboratory experiments that are normally covered in signals and systems courses and discusses how to run MATLAB codes for these experiments as apps on both Android and iOS smartphones, thus enabling a truly mobile laboratory paradigm. A zipped file of the codes discussed in the book can be acquired via the website http://sites.fastspring.com/bookcodes/product/SignalsSystemsBookcodesThirdEdition
Real-time or applied digital signal processing courses are offered as follow-ups to conventional or theory-oriented digital signal processing courses in many engineering programs for the purpose of teaching students the technical know-how for putting signal processing algorithms or theory into practical use. These courses normally involve access to a teaching laboratory that is equipped with hardware boards, in particular DSP boards, together with their supporting software. A number of textbooks have been written discussing how to achieve real-time implementation on these hardware boards. This book discusses how to use smartphones as hardware boards for real-time implementation of signal processing algorithms, thus providing an alternative to the hardware boards that are used in signal processing laboratory courses. The fact that mobile devices, in particular smartphones, have become powerful processing platforms led to the development of this book to enable students to use their own smartphones to run signal processing algorithms in real-time considering that these days nearly all students possess smartphones. Changing the hardware platforms that are currently used in applied or real-time signal processing courses to smartphones creates a truly flexible laboratory experience or environment for students. In addition, it relieves the cost burden associated with using dedicated signal processing boards noting that the software development tools for smartphones are free of charge and are well-maintained by smartphone manufacturers. This book is written in such a way that it can be used as a textbook for real-time or applied digital signal processing courses offered at many universities. Ten lab experiments that are commonly encountered in such courses are covered in the book. It is written primarily for those who are already familiar with signal processing concepts and are interested in their real-time and practical aspects. Similar to existing real-time courses, knowledge of C programming is assumed. This book can also be used as a self-study guide for those who wish to become familiar with signal processing app development on either Android or iOS smartphones/tablets.
Book Synopsis Smartphone-Based Real-Time Digital Signal Processing, Third Edition by : Abhishek Sehgal
Download or read book Smartphone-Based Real-Time Digital Signal Processing, Third Edition written by Abhishek Sehgal and published by Springer Nature. This book was released on 2022-05-31 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: Real-time or applied digital signal processing courses are offered as follow-ups to conventional or theory-oriented digital signal processing courses in many engineering programs for the purpose of teaching students the technical know-how for putting signal processing algorithms or theory into practical use. These courses normally involve access to a teaching laboratory that is equipped with hardware boards, in particular DSP boards, together with their supporting software. A number of textbooks have been written discussing how to achieve real-time implementation on these hardware boards. This book discusses how to use smartphones as hardware boards for real-time implementation of signal processing algorithms, thus providing an alternative to the hardware boards that are used in signal processing laboratory courses. The fact that mobile devices, in particular smartphones, have become powerful processing platforms led to the development of this book to enable students to use their own smartphones to run signal processing algorithms in real-time considering that these days nearly all students possess smartphones. Changing the hardware platforms that are currently used in applied or real-time signal processing courses to smartphones creates a truly flexible laboratory experience or environment for students. In addition, it relieves the cost burden associated with using dedicated signal processing boards noting that the software development tools for smartphones are free of charge and are well-maintained by smartphone manufacturers. This book is written in such a way that it can be used as a textbook for real-time or applied digital signal processing courses offered at many universities. Ten lab experiments that are commonly encountered in such courses are covered in the book. It is written primarily for those who are already familiar with signal processing concepts and are interested in their real-time and practical aspects. Similar to existing real-time courses, knowledge of C programming is assumed. This book can also be used as a self-study guide for those who wish to become familiar with signal processing app development on either Android or iOS smartphones/tablets.
This book introduces basic machine learning concepts and applications for a broad audience that includes students, faculty, and industry practitioners. We begin by describing how machine learning provides capabilities to computers and embedded systems to learn from data. A typical machine learning algorithm involves training, and generally the performance of a machine learning model improves with more training data. Deep learning is a sub-area of machine learning that involves extensive use of layers of artificial neural networks typically trained on massive amounts of data. Machine and deep learning methods are often used in contemporary data science tasks to address the growing data sets and detect, cluster, and classify data patterns. Although machine learning commercial interest has grown relatively recently, the roots of machine learning go back to decades ago. We note that nearly all organizations, including industry, government, defense, and health, are using machine learning to address a variety of needs and applications. The machine learning paradigms presented can be broadly divided into the following three categories: supervised learning, unsupervised learning, and semi-supervised learning. Supervised learning algorithms focus on learning a mapping function, and they are trained with supervision on labeled data. Supervised learning is further sub-divided into classification and regression algorithms. Unsupervised learning typically does not have access to ground truth, and often the goal is to learn or uncover the hidden pattern in the data. Through semi-supervised learning, one can effectively utilize a large volume of unlabeled data and a limited amount of labeled data to improve machine learning model performances. Deep learning and neural networks are also covered in this book. Deep neural networks have attracted a lot of interest during the last ten years due to the availability of graphics processing units (GPU) computational power, big data, and new software platforms. They have strong capabilities in terms of learning complex mapping functions for different types of data. We organize the book as follows. The book starts by introducing concepts in supervised, unsupervised, and semi-supervised learning. Several algorithms and their inner workings are presented within these three categories. We then continue with a brief introduction to artificial neural network algorithms and their properties. In addition, we cover an array of applications and provide extensive bibliography. The book ends with a summary of the key machine learning concepts.
Book Synopsis Machine and Deep Learning Algorithms and Applications by : Uday Shankar
Download or read book Machine and Deep Learning Algorithms and Applications written by Uday Shankar and published by Springer Nature. This book was released on 2022-05-31 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces basic machine learning concepts and applications for a broad audience that includes students, faculty, and industry practitioners. We begin by describing how machine learning provides capabilities to computers and embedded systems to learn from data. A typical machine learning algorithm involves training, and generally the performance of a machine learning model improves with more training data. Deep learning is a sub-area of machine learning that involves extensive use of layers of artificial neural networks typically trained on massive amounts of data. Machine and deep learning methods are often used in contemporary data science tasks to address the growing data sets and detect, cluster, and classify data patterns. Although machine learning commercial interest has grown relatively recently, the roots of machine learning go back to decades ago. We note that nearly all organizations, including industry, government, defense, and health, are using machine learning to address a variety of needs and applications. The machine learning paradigms presented can be broadly divided into the following three categories: supervised learning, unsupervised learning, and semi-supervised learning. Supervised learning algorithms focus on learning a mapping function, and they are trained with supervision on labeled data. Supervised learning is further sub-divided into classification and regression algorithms. Unsupervised learning typically does not have access to ground truth, and often the goal is to learn or uncover the hidden pattern in the data. Through semi-supervised learning, one can effectively utilize a large volume of unlabeled data and a limited amount of labeled data to improve machine learning model performances. Deep learning and neural networks are also covered in this book. Deep neural networks have attracted a lot of interest during the last ten years due to the availability of graphics processing units (GPU) computational power, big data, and new software platforms. They have strong capabilities in terms of learning complex mapping functions for different types of data. We organize the book as follows. The book starts by introducing concepts in supervised, unsupervised, and semi-supervised learning. Several algorithms and their inner workings are presented within these three categories. We then continue with a brief introduction to artificial neural network algorithms and their properties. In addition, we cover an array of applications and provide extensive bibliography. The book ends with a summary of the key machine learning concepts.
This book is designed for use as a textbook for a one semester Signals and Systems class. It is sufficiently user friendly to be used for self study as well. It begins with a gentle introduction to the idea of abstraction by looking at numbers—the one highly abstract concept we use all the time. It then introduces some special functions that are useful for analyzing signals and systems. It then spends some time discussing some of the properties of systems; the goal being to introduce the idea of a linear time-invariant system which is the focus of the rest of the book. Fourier series, discrete and continuous time Fourier transforms are introduced as tools for the analysis of signals. The concepts of sampling and modulation which are very much a part of everyday life are discussed as applications of the these tools. Laplace transform and Z transform are then introduced as tools to analyze systems. The notions of stability of systems and feedback are analyzed using these tools. The book is divided into thirty bite-sized modules. Each module also links up with a video lecture through a QR code in each module. The video lectures are approximately thirty minutes long. There are a set of self study questions at the end of each module along with answers to help the reader reinforce the concepts in the module.
Book Synopsis Signals and Systems by : Khalid Sayood
Download or read book Signals and Systems written by Khalid Sayood and published by Springer Nature. This book was released on 2022-06-01 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed for use as a textbook for a one semester Signals and Systems class. It is sufficiently user friendly to be used for self study as well. It begins with a gentle introduction to the idea of abstraction by looking at numbers—the one highly abstract concept we use all the time. It then introduces some special functions that are useful for analyzing signals and systems. It then spends some time discussing some of the properties of systems; the goal being to introduce the idea of a linear time-invariant system which is the focus of the rest of the book. Fourier series, discrete and continuous time Fourier transforms are introduced as tools for the analysis of signals. The concepts of sampling and modulation which are very much a part of everyday life are discussed as applications of the these tools. Laplace transform and Z transform are then introduced as tools to analyze systems. The notions of stability of systems and feedback are analyzed using these tools. The book is divided into thirty bite-sized modules. Each module also links up with a video lecture through a QR code in each module. The video lectures are approximately thirty minutes long. There are a set of self study questions at the end of each module along with answers to help the reader reinforce the concepts in the module.
Linear algebra is one of the most basic foundations of a wide range of scientific domains, and most textbooks of linear algebra are written by mathematicians. However, this book is specifically intended to students and researchers of pattern information processing, analyzing signals such as images and exploring computer vision and computer graphics applications. The author himself is a researcher of this domain. Such pattern information processing deals with a large amount of data, which are represented by high-dimensional vectors and matrices. There, the role of linear algebra is not merely numerical computation of large-scale vectors and matrices. In fact, data processing is usually accompanied with "geometric interpretation." For example, we can think of one data set being "orthogonal" to another and define a "distance" between them or invoke geometric relationships such as "projecting" some data onto some space. Such geometric concepts not only help us mentally visualize abstract high-dimensional spaces in intuitive terms but also lead us to find what kind of processing is appropriate for what kind of goals. First, we take up the concept of "projection" of linear spaces and describe "spectral decomposition," "singular value decomposition," and "pseudoinverse" in terms of projection. As their applications, we discuss least-squares solutions of simultaneous linear equations and covariance matrices of probability distributions of vector random variables that are not necessarily positive definite. We also discuss fitting subspaces to point data and factorizing matrices in high dimensions in relation to motion image analysis. Finally, we introduce a computer vision application of reconstructing the 3D location of a point from three camera views to illustrate the role of linear algebra in dealing with data with noise. This book is expected to help students and researchers of pattern information processing deepen the geometric understanding of linear algebra.
Book Synopsis Linear Algebra for Pattern Processing by : Kenichi Kanatani
Download or read book Linear Algebra for Pattern Processing written by Kenichi Kanatani and published by Springer Nature. This book was released on 2022-06-01 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear algebra is one of the most basic foundations of a wide range of scientific domains, and most textbooks of linear algebra are written by mathematicians. However, this book is specifically intended to students and researchers of pattern information processing, analyzing signals such as images and exploring computer vision and computer graphics applications. The author himself is a researcher of this domain. Such pattern information processing deals with a large amount of data, which are represented by high-dimensional vectors and matrices. There, the role of linear algebra is not merely numerical computation of large-scale vectors and matrices. In fact, data processing is usually accompanied with "geometric interpretation." For example, we can think of one data set being "orthogonal" to another and define a "distance" between them or invoke geometric relationships such as "projecting" some data onto some space. Such geometric concepts not only help us mentally visualize abstract high-dimensional spaces in intuitive terms but also lead us to find what kind of processing is appropriate for what kind of goals. First, we take up the concept of "projection" of linear spaces and describe "spectral decomposition," "singular value decomposition," and "pseudoinverse" in terms of projection. As their applications, we discuss least-squares solutions of simultaneous linear equations and covariance matrices of probability distributions of vector random variables that are not necessarily positive definite. We also discuss fitting subspaces to point data and factorizing matrices in high dimensions in relation to motion image analysis. Finally, we introduce a computer vision application of reconstructing the 3D location of a point from three camera views to illustrate the role of linear algebra in dealing with data with noise. This book is expected to help students and researchers of pattern information processing deepen the geometric understanding of linear algebra.
With its exhaustive coverage of relevant theory, Signals and Systems Laboratory with MATLAB® is a powerful resource that provides simple, detailed instructions on how to apply computer methods to signals and systems analysis. Written for laboratory work in a course on signals and systems, this book presents a corresponding MATLAB implementation for each theoretical concept introduced, making it a powerful learning tool for engineers, scientists, and students alike. MATLAB code is used in problems and examples presented throughout the book. This code and other learning materials are available in a downloadable supplement. Due to the extensive—and truly unique—integration of MATLAB throughout this book, the authors provide a complete tutorial on use of the language for signals and systems analysis. With more than 5,000 lines of MATLAB code and more than 700 figures embedded in the text, the material teaches readers how to program in MATLAB and study signals and systems concepts at the same time, giving them the tools to harness the power of computers to quickly assess problems and then visualize their solutions. Among its many useful features, this book: Offers complete coverage of the signals and systems theory, starting with elementary signals and concluding with state-space modeling Contains more than 400 examples and chapter-end solved problems Executes commands one-by-one at the MATLAB command prompt, and results, along with comments, encouraging students to learn MATLAB on the fly Additional Pedagogical Features: A detailed MATLAB tutorial to introduce a beginner programmer to the language Laboratory exercises that give students hands-on experience and help professors organize a course laboratory component Presentation of continuous- and discrete-time in parallel fashion, effectively illustrating the similarities and differences between the two Step-by-step examples that present data in tabular format and usually offer several different solutions to each problem
Book Synopsis Signals and Systems Laboratory with MATLAB by : Alex Palamides
Download or read book Signals and Systems Laboratory with MATLAB written by Alex Palamides and published by CRC Press. This book was released on 2010-08-13 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: With its exhaustive coverage of relevant theory, Signals and Systems Laboratory with MATLAB® is a powerful resource that provides simple, detailed instructions on how to apply computer methods to signals and systems analysis. Written for laboratory work in a course on signals and systems, this book presents a corresponding MATLAB implementation for each theoretical concept introduced, making it a powerful learning tool for engineers, scientists, and students alike. MATLAB code is used in problems and examples presented throughout the book. This code and other learning materials are available in a downloadable supplement. Due to the extensive—and truly unique—integration of MATLAB throughout this book, the authors provide a complete tutorial on use of the language for signals and systems analysis. With more than 5,000 lines of MATLAB code and more than 700 figures embedded in the text, the material teaches readers how to program in MATLAB and study signals and systems concepts at the same time, giving them the tools to harness the power of computers to quickly assess problems and then visualize their solutions. Among its many useful features, this book: Offers complete coverage of the signals and systems theory, starting with elementary signals and concluding with state-space modeling Contains more than 400 examples and chapter-end solved problems Executes commands one-by-one at the MATLAB command prompt, and results, along with comments, encouraging students to learn MATLAB on the fly Additional Pedagogical Features: A detailed MATLAB tutorial to introduce a beginner programmer to the language Laboratory exercises that give students hands-on experience and help professors organize a course laboratory component Presentation of continuous- and discrete-time in parallel fashion, effectively illustrating the similarities and differences between the two Step-by-step examples that present data in tabular format and usually offer several different solutions to each problem
