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Hands-On Neural Network Programming with C#

You're reading from  Hands-On Neural Network Programming with C#

Product type Book
Published in Sep 2018
Publisher Packt
ISBN-13 9781789612011
Pages 328 pages
Edition 1st Edition
Languages
Author (1):
Matt Cole Matt Cole
Profile icon Matt Cole

Table of Contents (16) Chapters

Preface A Quick Refresher Building Our First Neural Network Together Decision Trees and Random Forests Face and Motion Detection Training CNNs Using ConvNetSharp Training Autoencoders Using RNNSharp Replacing Back Propagation with PSO Function Optimizations: How and Why Finding Optimal Parameters Object Detection with TensorFlowSharp Time Series Prediction and LSTM Using CNTK GRUs Compared to LSTMs, RNNs, and Feedforward networks Activation Function Timings
Function Optimization Reference Other Books You May Enjoy

The Rotated Hyper-Ellipsoid function

The following is the Rotated Hyper-Ellipsoid function

Rotated Hyper-Ellipsoid Function

Description

Dimensions: d
The Rotated Hyper-Ellipsoid function is continuous, convex, and unimodal. It is an extension of the Axis Parallel Hyper-Ellipsoid function, also referred to as the Sum Squares function. The plot shows its two-dimensional form.

Input domain

The function is usually evaluated on the xi ∈ [-65.536, 65.536] hypercube, for all i = 1, …, d.

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