 Home | Amazing | Today | Tags | Publishers | Years | Account | Search      An Introduction to Parametric Digital Filters and Oscillators    Since the 1960s Digital Signal Processing (DSP) has been one of the most intensive fields of study in electronics. However, little has been produced specifically on linear non-adaptive time-variant digital filters. The first book to be dedicated to Time-Variant Filtering Provides a complete...   Linear and Nonlinear Multivariable Feedback Control: A Classical Approach Automatic feedback control systems play crucial roles in many fields, including manufacturing industries, communications, naval and space systems. At its simplest, a control system represents a feedback loop in which the difference between the ideal (input) and actual (output) signals is used to modify the behaviour of the system. Control...   Geometric Algorithms and Combinatorial Optimization (Algorithms and Combinatorics 2) This book develops geometric techniques for proving the polynomial time solvability of problems in convexity theory, geometry, and - in particular - combinatorial optimization. It offers a unifying approach based on two fundamental geometric algorithms: - the ellipsoid method for finding a point in a convex set and - the basis reduction...  Introductory Statistics with R (Statistics and Computing) This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the...   Analysis and Control of Nonlinear Process Systems (Advanced Textbooks in Control and Signal Processing)Almost all process systems are nonlinear in nature. Nonlinear control is traditionally an area of interest in process systems engineering which is of great practical importance. These facts notwithstanding, many process engineers have difficulty with the paradigms and results of modern nonlinear control theory because they lack the mathematical...   Differential Equations For DummiesPower your way through ordinary and singular points Understand differential equations through practical tips and examples Do differential equations cause you distress? No worries! This friendly guide explains this intimidating subject in plain English, walking you step by step through all...  Bioinformatics: High Performance Parallel Computer Architectures (Embedded Multi-Core Systems) New sequencing technologies have broken many experimental barriers to genome scale sequencing, leading to the extraction of huge quantities of sequence data. This expansion of biological databases established the need for new ways to harness and apply the astounding amount of available genomic information and convert it into substantive...   Discontinuity and Complexity in Nonlinear Physical Systems Discontinuity in Nonlinear Physical Systems explores recent developments in experimental research in this broad field, organized in four distinct sections. Part I introduces the reader to the fractional dynamics and Lie group analysis for nonlinear partial differential equations. Part II covers chaos and complexity in nonlinear Hamiltonian...   MATLAB Linear Algebra MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or... Hands-On Machine Learning for Algorithmic Trading: Design and implement investment strategies based on smart algorithms that learn from data using Python

Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras

#### Key Features

• Implement machine learning algorithms to build, train, and validate algorithmic models
• Create your own algorithmic design process to apply...  An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most...  Partial Differential Equations and the Finite Element Method
A systematic introduction to partial differential equations and modern finite element methods for their efficient numerical solution

Partial Differential Equations and the Finite Element Method provides a much-needed, clear, and systematic introduction to modern theory of partial differential equations (PDEs) and... Result Page: 67 66 65 64 63 62 61 60 59 58 57 56 55 54 53 52 51 50