Machine Learning by
Machine Learning: Theory and Practice provides an introduction to the most popular methods in machine learning. The book covers regression including regularization, tree-based methods including Random Forests and Boosted Trees, Artificial Neural Networks including Convolutional Neural Networks (CNNs), reinforcement learning, and unsupervised learning focused on clustering. Topics are introduced in a conceptual manner along with necessary mathematical details. The explanations are lucid, illustrated with figures and examples. For each machine learning method discussed, the book presents appropriate libraries in the R programming language along with programming examples. Features: Provides an easy-to-read presentation of commonly used machine learning algorithms in a manner suitable for advanced undergraduate or beginning graduate students, and mathematically and/or programming-oriented individuals who want to learn machine learning on their own. Covers mathematical details of the machine learning algorithms discussed to ensure firm understanding, enabling further exploration Presents worked out suitable programming examples, thus ensuring conceptual, theoretical and practical understanding of the machine learning methods. This book is aimed primarily at introducing essential topics in Machine Learning to advanced undergraduates and beginning graduate students. The number of topics has been kept deliberately small so that it can all be covered in a semester or a quarter. The topics are covered in depth, within limits of what can be taught in a short period of time. Thus, the book can provide foundations that will empower a student to read advanced books and research papers.
Modern Information Optics with MATLAB by
An easy-to-understand course book, based on the authentic lectures and detailed research, conducted by the authors themselves, on information optics, holography and MATLAB. This book is the first to highlight the incoherent optical system, provide up-to-date, novel digital holography techniques, and demonstrate MATLAB codes to accomplish tasks such as optical image processing and pattern recognition. This title is a comprehensive introduction to the basics of Fourier optics as well as optical image processing and digital holography. A step-by-step guide which details the vast majority of the derivations, without omitting essential steps, to facilitate a clear mathematical understanding. This book also features exercises at the end of each chapter, providing hands-on experience and consolidating understanding. An ideal companion for graduates and researchers involved in engineering and applied physics, as well as interested in the growing field of information optics.
Nanostructured Gas Sensors by
Nanostructured materials exhibit distinct properties by virtue of their nanoscale morphological variations, which open up endless possibilities to investigate unexplored and interesting applications. This textbook broadly covers the fabrication and characterization of nanostructured films and exploration of their gas-sensing applications. It presents the fundamentals of gas-sensing technology and a comprehensive study on smart gas sensing technology. Readers will find basics, analytical techniques, nanotechnology-enabled experimental findings, and future directions of smart gas-sensing technology at one place. Through the inclusion of up-to-date experimental knowledge of synthesis, processing, and application development, the book is suitable for academics at all levels.
Fourier Theory in Optics and Optical Information Processing by
Fourier analysis is one of the most important concepts when you apply physical ideas to engineering issues. This book provides a comprehensive understanding of Fourier transform and spectral analysis in optics, image processing, and signal processing. Written by a world renowned author, this book looks to unify the readers understanding of principles of optics, information processing and measurement. This book describes optical imaging systems through a linear system theory. The book also provides an easy understanding of Fourier transform and system theory in optics. It also provides background of optical measurement and signal processing. Finally, the author also provides a systematic approach to learning many signal processing techniques in optics. The book is intended for researchers, industry professionals, and graduate level students in optics and information processing.
Gas Sensors by
Covers detailed state-of-the-art of specific chemiresistive sensing materials Presents novel nano-material platforms and concepts for resistive gas sensing Reviews pertinent aspects of smart sensors and IoT sensing Explains nanotechnology enabled experimental findings, and future directions of smart gas sensing technology Explores implication of latest advancements such as IoT in Gas sensors, and nanogenerators
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