Learn IT - Books tags linear

Optimal and Robust Control: Advanced Topics with MATLAB®

CRC Press, 2012

While there are many books on advanced control for specialists, there are few that present these topics for nonspecialists. Assuming only a basic knowledge of automatic control and signals and systems, Optimal and Robust Control: Advanced Topics with MATLAB^® offers a straightforward, self-contained...

Modular Algorithms in Symbolic Summation and Symbolic Integration (Lecture Notes in Computer Science)

Springer, 2005

This work brings together two streams in computer algebra: symbolic integration and summation on the one hand, and fast algorithmics on the other hand. In many algorithmically oriented areas of computer science, theanalysisof- gorithms–placedintothe limelightbyDonKnuth’stalkat the 1970ICM –provides a crystal-clear criterion for...

Statistical Tools for Nonlinear Regression: A Practical Guide With S-PLUS and R Examples (Springer Series in Statistics)

Springer, 2003

Statistical Tools for Nonlinear Regression presents methods for analyzing data. It has been expanded to include binomial, multinomial and Poisson non-linear models. The examples are analyzed with the free software nls2 updated to deal with the new models included in the second edition. The nls2 package is implemented in S-PLUS and R....

Mathematical Methods and Algorithms for Signal Processing

Pearson Education, 1999

Mathematical Methods and Algorithms for Signal Processing tackles the challenge of providing readers and practitioners with the broad tools of mathematics employed in modern signal processing. Building from an assumed background in signals and stochastic processes, the book provides a solid foundation in analysis, linear...

Maximum Likelihood Estimation and Inference: With Examples in R, SAS and ADMB

John Wiley & Sons, 2011

This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodology, including general latent variable...

An Introduction to Analysis of Financial Data with R

John Wiley & Sons, 2012

A complete set of statistical tools for beginning financial analysts from a leading authority

Written by one of the leading experts on the topic, An Introduction to Analysis of Financial Data with R explores basic concepts of visualization of financial data. Through a fundamental balance between theory and...

Deep Learning with TensorFlow: Explore neural networks and build intelligent systems with Python, 2nd Edition

Packt Publishing, 2018

Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow.

Key Features

Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow

Explore deep neural...

Hands-On Reinforcement Learning with Python: Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow

Packt Publishing, 2018

A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python

Key Features

Enter the world of artificial intelligence using the power of Python

An example-rich guide to master various RL and DRL algorithms

Explore...

TensorFlow 2.0 Quick Start Guide: Get up to speed with the newly introduced features of TensorFlow 2.0

Packt Publishing, 2019

Perform supervised and unsupervised machine learning and learn advanced techniques such as training neural networks.

Key Features

Train your own models for effective prediction, using high-level Keras API

Perform supervised and unsupervised machine learning and learn...

Scientific Computing with MATLAB and Octave (Texts in Computational Science and Engineering)

Springer, 2010

This textbook is an introduction to Scientific Computing, in which several numerical methods for the computer-based solution of certain classes of mathematical problems are illustrated. The authors show how to compute the zeros or the integrals of continuous functions, solve linear systems, approximate functions using polynomials and...

Numerical Methods Using MATLAB (3rd Edition)

Prentice Hall, 1998

This introduction to numerical analysis shows how the mathematics of calculus and linear algebra are implemented in computer algorithms. It develops a deep understanding of why numerical methods work and exactly what their limitations are....

Automatic Control of Atmospheric and Space Flight Vehicles: Design and Analysis with MATLAB® and Simulink® (Control Engineering)

Birkhauser, 2011

The main purpose of writing this book is to present a unified approach for automatic control of atmospheric and space flight vehicles. Such an outlook has become more necessary nowthan ever,with the advent of aerospace vehicleswhose singlemission covers operation as aircraft, rocket, and spacecraft at various instants....

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