Signal and Image Processing with Neural Networks: A C++ Sourcebook
Product Description
Signal and Image Processing with Neural Networks: A C++ Sourcebook
Demonstrates how neural networks can be used to aid in the solution of digital signal processing (DSP) or imaging problems. A large section is devoted to the design and training of complex-domain multiple-layer feedforward networks (MLFNs)—all essential equations are presented and justified. Reviews the most popular signal- and image-processing algorithms, emphasizing those that are particularly suitable for union to complex-domain neural networks. Features a wide variety of problems for which complex-domain networks significantly outperform their real-domain counterparts. The accompanying disk includes complete source code for algorithms discussed with full source for program examples.
Technical Specifications
You might also like
Advanced Algorithms for Neural Networks: A C++ Sourcebook
Practical Neural Network Recipies in C++
Neural, Novel & Hybrid Algorithms for Time Series Prediction
Deep Belief Nets in C++ and CUDA C: Volume 1: Restricted Boltzmann Machines and Supervised Feedforward Networks
Assessing and Improving Prediction and Classification
Deep Belief Nets in C++ and CUDA C: Volume II: Autoencoding in the Complex Domain (Volume 2)
Deep Belief Nets in C++ and CUDA C: Volume III: Convolutional Nets (Volume 3)
Python Machine Learning
Neural Networks for Pattern Recognition (Advanced Texts in Econometrics (Paperback))
Object-Oriented Neural Networks in C++