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Gesamtkatalog

Catalogue complet

Nahin Paul J.: The Mathematical Radio

The Mathematical Radio

Inside the Magic of AM, FM, and Single-Sideband

This unique compendium consists of two parts - electric circuit and fundamentals of transmission theory. The first part contains all the necessary materials to understand electric circuit and emphasizes on numerical method and calculation using Python program. The crucial second part starts with Maxwell equations to treat the electromagnetic phenomena of conducting materials and derives the Heaviside equation for transmission theory in distributed-parameter circuit. Boundary condition of the lumped and distributed circuits are introduced. The boundary condition enables readers to understand the source of electric noise from circuit.This useful reference text will benefit researchers, professionals, engineers, advanced undergraduate and graduate students in the field of circuits &amp; systems.

Fundamentals Of Electric Circuits And Transmission Lines

FPGA, IoT, Microcontrollers, and Quantum Technologies

Exploring Hardware Advances

An Introduction to the Finite Element Method with the Variational Approach offers a comprehensive solution to the gaps often found in introductory texts on the Finite Element Method (FEM). The book provides a thorough introduction to the fundamental principles of linear and time-independent FEM within the variational framework. It meticulously covers the derivation of 1-D FEM equations based on variational functionals, encompassing both linear and higher-order elements, and shape functions driven by convergence criteria. Furthermore, it explores 1-D numerical integration, outlines coding procedures, and provides insights into handling material nonlinearity and time-dependent scenarios. Expanding into 2-D problems, the book offers derivations of 2-D FEM equations tailored to diverse engineering disciplines, including Steady-State Heat Conduction, Solid Mechanics (covering torsion, plane strain/axisymmetric cases, and the bending, stability, and vibrations of thin plates), as well as Fluid Mechanics (addressing incompressible inviscid and viscous fluids). It includes detailed discussions on element continuity, numerical integration techniques, and even includes 2-D codes for selected problems. The book concludes by delving into recent advancements in FEM, with a specific focus on applications in machine learning and isogeometric analysis.

An Introduction to the Finite Element Method with the Variational Approach

Industrial Electronics

Beginning with a thorough discussion of electromagnetics, the book achieves two primary objectives. First, the book develops an understanding of electric and magnetic fields so that readers can connect the structure of electromagnetic fields to circuit structures and their lumped element models. Second, it allows the user to gain sufficient facility with electromagnetic waves to appreciate phenomena associated with waves traveling in circuits and on printed circuit boards such as reflection, transmission, dispersion, and loss.

Beginning with a thorough discussion of electromagnetics, the book achieves two primary objectives. First, the book develops an understanding of electric and magnetic fields so that readers can connect the structure of electromagnetic fields to circuit structures and their lumped element models. Second, it allows the user to gain sufficient facility with electromagnetic waves to appreciate phenomena associated with waves traveling in circuits and on printed circuit boards such as reflection, transmission, dispersion, and loss.

Principles and Practice

Signal Integrity in Digital Systems

Tiny Machine Learning Techniques for Constrained Devices

Integrated Photonics: Application-Specific Design and Manufacturing

Photonic Integrated Circuits for Sensing Applications delves into the fascinating world of sensors within the realm of integrated photonics. The book begins with a historical overview, tracing the evolution of spectroscopic sensing techniques such as FTIR, Raman, SPR, and reflectometry, each contributing to the field’s growth. It emphasizes the transformative potential of photonic integrated circuit (PIC) sensor systems by showcasing their advantages in achieving low SWAP-C metrics (size, weight, power, and cost) while maintaining high performance. Complete with technical insights, the book sets the stage for understanding how PICs are revolutionizing sensing applications across diverse industries. Beyond the introductory scope, the book thoroughly examines the components that constitute PIC sensor systems, including waveguides (operating below and above 1550 nm), ring resonators, photonic crystals, and MZ interferometers. It also explores integrated systems designed for chem-bio sensing applications, leveraging biofunctionalization and sorbent technologies. With attention to manufacturing scalability, topics such as materials, PDK development, and sensor packaging are addressed, ensuring readers grasp the practical aspects of producing advanced sensor systems at scale.

Integrated Photonics for SENSING APPLICATIONS

Mathematics and Biomedical Engineering in Medicine, Physiology and Health Sciences is a visionary book, whose purpose is to demonstrate how fundamental mathematics and biomedical engineering can be incorporated into physiology, medicine, and health sciences teaching, research, and clinical practice to make these disciplines more quantitative and computational, and hence more explanatory and informative. The book also provides more quantitative formulation of medical procedures, towards supporting the growing field of precision medicine.

Mathematics and Biomedical Engineering in Medicine, Physiology and Health Sciences

Why Not Nonlinear Algebra: Math, Science, Applications And Funding

This hands-on, beginner-friendly book guides hobbyists and makers through every step of creating a custom printed circuit board (PCB), from conception through production. Based on a popular university course, this book is a fun, practical guide to designing printed circuit boards (PCBs) for readers of all skill levels – no industry experience required. Readers will learn to transform a breadboard prototype into a professional-grade PCB. More than that, this book bridges the gap between a basic understanding of electronic design and the methods used to manufacture those designs in a reliable, consistent, and scalable manner. Software-agnostic exercises are provided throughout, allowing readers to try out new concepts no matter what design platform is used. By the end, they’ll be ready to develop their own custom electronics.

Practical PCB Design

Extended Hypergeometric Functions and Orthogonal Polynomials

While the field of Deep Learning has been advancing at frightening speeds during the last ten years, we do not have a plausible theoretical explanation of its success yet. One can safely say that Deep Learning works, but nobody really understands why. Nevertheless, starting around five years before now, a decent number of theoretical papers specifically concerning neural nets started to emerge at top machine learning venues. This makes us think that the core of Deep Learning theory has already started to crystallize.The goal of the present book is to present these core concepts of Deep Learning theory to readers so that they could directly dive into recent papers of this area. For this purpose, each chapter elaborates a simple model or a classical result in details first and then discusses possible generalizations and more recent developments of the same idea.We have to warn the reader that the present book is not a mathematical manuscript. Not all results here are stated as formal theorems and not all theorems are provided with complete and rigorous proofs. Many of the theorems of the book are proven up to some technical lemmas, while for some there is only a proof sketch. This conforms with the main idea of the book: present and illustrate concepts rather than reproduce all the results.The book, in its present form, covers the following topics: uniform generalization bounds, PAC-bayesian generalization bounds, double descent phenomena, infinitely-wide networks, implicit bias of gradient descent, loss landscape, gradient descent convergence guarantees, and initialization strategies.

Elements Of Deep Learning Theory

Data Science and Interactive Visualization Tools for the Analysis of Qualitative Evidence empowers qualitative and mixed methods researchers in the data science movement by offering no-code, cost-free software access so that they can apply cutting-edge and innovative methods to synthetize qualitative data. The book builds on the idea that qualitative and mixed methods researchers should not have to learn to code to benefit from rigorous open-source, cost-free software that uses artificial intelligence, machine learning, and data visualization tools-just as people do not need to know C++ or TypeScript to benefit from Microsoft Word. The real barrier is the hundreds of R code lines required to apply these concepts to their databases. By removing the coding proficiency hurdle, this book will empower their research endeavors and help them become active members of and contributors to the applied data science community. The book offers a comprehensive explanation of data science and machine learning methodologies, along with access to software application tools to implement these techniques without any coding proficiency. The book addresses the need for innovative tools that enable researchers to tap into the insights that come out of cutting-edge data science tools with absolutely no computer language literacy requirements.

Data Science and Interactive Visualization Tools for the Analysis of Qualitative Evidence

The Mathematical Radio

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