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Digital Signal Processing Techniques and Applications in Radar Image Processing (Information and Communication Technology Series,)
Digital Signal Processing Techniques and Applications in Radar Image Processing (Information and Communication Technology Series,)
A self-contained approach to DSP techniques and applications in radar imaging

The processing of radar images, in general, consists of three major fields: Digital Signal Processing (DSP); antenna and radar operation; and algorithms used to process the radar images. This book brings together material from these different areas to allow readers to...

Python Data Analysis Cookbook
Python Data Analysis Cookbook

Key Features

  • Analyze Big Data sets, create attractive visualizations, and manipulate and process various data types
  • Packed with rich recipes to help you learn and explore amazing algorithms for statistics and machine learning
  • Authored by Ivan Idris, expert in python programming and proud...
OpenCL Programming by Example
OpenCL Programming by Example

For a comprehensive, easy-to-swallow guide to OpenCL Programming, this book is out on its own. That's because it teaches through examples and covers everything from parallel sorting to optimization in simple stages.

Overview

  • Learn about all of the OpenCL Architecture and major APIs.
  • ...
Big Data Analytics with Hadoop 3: Build highly effective analytics solutions to gain valuable insight into your big data
Big Data Analytics with Hadoop 3: Build highly effective analytics solutions to gain valuable insight into your big data

Explore big data concepts, platforms, analytics, and their applications using the power of Hadoop 3

Key Features

  • Learn Hadoop 3 to build effective big data analytics solutions on-premise and on cloud
  • Integrate Hadoop with other big data tools such as R, Python, Apache...
Hadoop Backup and Recovery solutions
Hadoop Backup and Recovery solutions

Learn the best strategies for data recovery from Hadoop backup clusters and troubleshoot problems

About This Book

  • Learn the fundamentals of Hadoop's backup needs, recovery strategy, and troubleshooting
  • Determine common failure points, intimate HBase, and explore different backup...
Programming Arduino Next Steps: Going Further with Sketches
Programming Arduino Next Steps: Going Further with Sketches

Take your Arduino skills to the next level!

In this practical guide, electronics guru Simon Monk takes you under the hood of Arduino and reveals professional programming secrets. Featuring coverage of the Arduino Uno, Leonardo, and Due boards, Programming Arduino Next Steps: Going Further with Sketches shows you how to use...

Hadoop Real World Solutions Cookbook - Second Edition
Hadoop Real World Solutions Cookbook - Second Edition

Key Features

  • Implement outstanding Machine Learning use cases on your own analytics models and processes.
  • Solutions to common problems when working with the Hadoop ecosystem.
  • Step-by-step implementation of end-to-end big data use cases.

Who This Book Is For

...

Neural Networks: Computational Models and Applications (Studies in Computational Intelligence)
Neural Networks: Computational Models and Applications (Studies in Computational Intelligence)

Artificial neural networks, or simply called neural networks, refer to the various mathematical models of human brain functions such as perception, computation and memory. It is a fascinating scientific challenge of our time to understand how the human brain works. Modeling neural networks facilitates us in investigating the...

Deep Learning with Applications Using Python: Chatbots and Face, Object, and Speech Recognition With TensorFlow and Keras
Deep Learning with Applications Using Python: Chatbots and Face, Object, and Speech Recognition With TensorFlow and Keras
Explore deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications....
Hands-On Markov Models with Python: Implement probabilistic models for learning complex data sequences using the Python ecosystem
Hands-On Markov Models with Python: Implement probabilistic models for learning complex data sequences using the Python ecosystem

Unleash the power of unsupervised machine learning in Hidden Markov Models using TensorFlow, pgmpy, and hmmlearn

Key Features

  • Build a variety of Hidden Markov Models (HMM)
  • Create and apply models to any sequence of data to analyze, predict, and extract valuable...
Massively Parallel Evolutionary Computation on GPGPUs (Natural Computing Series)
Massively Parallel Evolutionary Computation on GPGPUs (Natural Computing Series)

Evolutionary algorithms (EAs) are metaheuristics that learn from natural collective behavior and are applied to solve optimization problems in domains such as scheduling, engineering, bioinformatics, and finance. Such applications demand acceptable solutions with high-speed execution using finite computational resources. Therefore, there have...

Coding Theory: Algorithms, Architectures and Applications
Coding Theory: Algorithms, Architectures and Applications
One of the most important key technologies for digital communication systems as well as storage media is coding theory. It provides a means to transmit information across time and space over noisy and unreliable communication channels.

Coding Theory: Algorithms, Architectures and Applications provides a concise overview...

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