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Featuring a focus on the student, this book lets students teach the science of circuit analysis to themselves. It features simple practice problems appearing throughout each chapter, while more difficult problems appear at the ends of chapters, following the order of presentation of text material.
Irwin's Basic Engineering Circuit Analysis has built a solid reputation for its highly accessible presentation, clear explanations, and extensive array of helpful learning aids. Now in a new eighth edition, this highly accessible book has been fine-tuned and revised, making it more effective and even easier to use. It covers such topics as resistive circuits, nodal and loop analysis techniques, capacitance and inductance, AC steady-state analysis, polyphase circuits, the Laplace transform, two-port networks, and much more.
Praise for the Second Edition: "The authors present an intuitive and easy-to-read book. ... accompanied by many examples, proposed exercises, good references, and comprehensive appendices that initiate the reader unfamiliar with MATLAB." —Adolfo Alvarez Pinto, International Statistical Review "Practitioners of EDA who use MATLAB will want a copy of this book. ... The authors have done a great service by bringing together so many EDA routines, but their main accomplishment in this dynamic text is providing the understanding and tools to do EDA. —David A Huckaby, MAA Reviews Exploratory Data Analysis (EDA) is an important part of the data analysis process. The methods presented in this text are ones that should be in the toolkit of every data scientist. As computational sophistication has increased and data sets have grown in size and complexity, EDA has become an even more important process for visualizing and summarizing data before making assumptions to generate hypotheses and models. Exploratory Data Analysis with MATLAB, Third Edition presents EDA methods from a computational perspective and uses numerous examples and applications to show how the methods are used in practice. The authors use MATLAB code, pseudo-code, and algorithm descriptions to illustrate the concepts. The MATLAB code for examples, data sets, and the EDA Toolbox are available for download on the book’s website. New to the Third Edition Random projections and estimating local intrinsic dimensionality Deep learning autoencoders and stochastic neighbor embedding Minimum spanning tree and additional cluster validity indices Kernel density estimation Plots for visualizing data distributions, such as beanplots and violin plots A chapter on visualizing categorical data
The hallmark feature of this classic text is its focus on the student â¬" it is written so that students may teach the science of circuit analysis to themselves. Terms are clearly defined when they are introduced, basic material appears toward the beginning of each chapter and is explained carefully and in detail, and numerical examples are used to introduce and suggest general results. Simple practice problems appear throughout each chapter, while more difficult problems appear at the ends of chapters, following the order of presentation of text material. This introduction and resulting repetition provide an important boost to the learning process. Hayt's rich pedagogy supports and encourages the student throughout by offering tips and warnings, using design to highlight key material, and providing lots of opportunities for hands-on learning. The thorough exposition of topics is delivered in an informal way that underscores the authorsâ¬" conviction that circuit analysis can and should be fun.