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Self-Learning and Adaptive Algorithms for Business Applications

with the help of traditional techniques. Self-learning and adaptive algorithms are now widely used by such leading giants that as Google, Tesla;

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Adaptive Machine Learning Algorithms with Python

adaptive machine learning and data analytics problems and be able to derive new algorithms for your own use cases. You will also come away with;

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Learning Algorithms

the theory and applications of learning algorithms-stochastic learning automata; artificial neural networks; and genetic algorithms;

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Self-Learning Control of Finite Markov Chains

Presents a number of new and potentially useful self-learning (adaptive) control algorithms and theoretical as well as practical results;

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Self-Learning Control of Finite Markov Chains

Presents a number of new and potentially useful self-learning (adaptive) control algorithms and theoretical as well as practical results;

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Kernel Adaptive Filtering

Reproducing kernel Hilbert spaces is a topic of great current interest for applications in signal processing, communications, and controls;

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Big Data Analytics with Applications in Insider Threat Detection

Today's malware mutates randomly to avoid detection, but reactively adaptive malware is more intelligent, learning and adapting to new;

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Trends in Deep Learning Methodologies

predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive;

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Introduction to Deep Learning Business Applications for Developers

personal assistants, automated translation, and autonomous vehicles. An Introduction to Deep Learning Business Applications for Developers covers;

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Self-Adaptive Heuristics For Evolutionary Computation

not achieved the attention it deserves. This book introduces various types of self-adaptive parameters for evolutionary computation;

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Optimal and Adaptive Signal Processing

algorithm, applications of adaptive filtering, algorithms and structures for adaptive filtering, spectral analysis, and array signal processing;

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Optimal and Adaptive Signal Processing

algorithm, applications of adaptive filtering, algorithms and structures for adaptive filtering, spectral analysis, and array signal processing;

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Self-Adaptive Systems for Machine Intelligence

This book will advance the understanding and application of self-adaptive intelligent systems; therefore it will potentially benefit the;

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Computational Intelligence Applications in Business Intelligence and Big Data Analytics

than provide an in-depth exploration in learning and adaptive mechanisms. This book sets its focus on CI based architectures, modeling, case;

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Adaptive Learning Methods for Nonlinear System Modeling

Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning;

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Evolutionary Programming IV

in Evolutionary Optimization Pattern Discovery, Pattern Recognition, and System Identification.- Hierarchical Levels of Learning.- Self-Adaptation;

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Self-Tuning Systems

Geared to the usersa needs, this work provides comprehensive coverage of the main techniques and methods necessary to construct a self;

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Adaptive Filtering

In the fourth edition of Adaptive Filtering: Algorithms and Practical Implementation, author Paulo S.R. Diniz presents the basic concepts;

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Partial Update Least-Square Adaptive Filtering

). Therefore, analyses for PU least-squares adaptive filter algorithms are necessary and meaningful. This monograph mostly focuses on the analyses;

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Partial Update Least-Square Adaptive Filtering

). Therefore, analyses for PU least-squares adaptive filter algorithms are necessary and meaningful. This monograph mostly focuses on the analyses;

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Adaptive Filtering Prediction and Control

-time systems. Their approach summarizes the theoretical and practical aspects of a large class of adaptive algorithms.Ideal for advanced;

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Adaptive Approach to Petroleum Reservoir Simulation

This book presents unique features of the adaptive modeling approach based on new machine learning algorithms for petroleum exploration;

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Adaptive Approach to Petroleum Reservoir Simulation

This book presents unique features of the adaptive modeling approach based on new machine learning algorithms for petroleum exploration;

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Adversarial Robustness for Machine Learning

Adversarial Robustness for Machine Learning summarizes the recent progress on this topic and introduces popular algorithms on;

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Adaptive Filtering

and adaptive filtering. He first introduces the main classes of adaptive filtering algorithms in a unified framework, using clear notations;

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Adaptive Filtering

and adaptive filtering. He first introduces the main classes of adaptive filtering algorithms in a unified framework, using clear notations;

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Proportionate-type Normalized Least Mean Square Algorithms

. These algorithms offer low computational complexity and fast convergence times for sparse impulse responses in network and acoustic echo;

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