Multilayer neural network model

Ebook "Neural networks - A comprehensive foundation" includes content: Introduction, learning processes; single layer perceptrons; multilayer perceptrons; radial basis function networks; support vector machines; committee machines; principal components analysis; self organizing maps; information theoretic models; stochastic machines and their approximates rooted in statistical mechanics; neurodynamic programming; temporal processing using feedforward networks; neurodynamics; dynamically driven recurrent networks.

823p haojiubujain07 20-09-2023 6 2   Download

This paper proposes a Multilayer Feed forward Neural Network (MLFNN) for speech classification in a smart electric wheelchair, in which with extraction of speech commands is performed using a Mel Frequency Cepstral Coefficients (MMFC) method.

7p vidoctorstrange 06-05-2023 7 4   Download

We collected information on patients with rectal adenocarcinoma in the United States from the Surveillance, Epidemiology, and EndResults (SEER) database. We used this information to establish a model that combined deep learning with a multilayer neural network (the DeepSurv model) for predicting the survival rate of patients with rectal adenocarcinoma.

14p vipriyankagandhi 27-07-2022 7 2   Download

In this paper, we propose a multilayer neural network model for generating SpamAssassin rules which selects good features and optimize rule weights at the same time. The weighted rule set obtained from training this neural network can be applied directly in SpamAssassin. The experiments showed that our network is fast to train and the resulted rule set has comparable detection rates to previous rule generation methods.

8p viaespa2711 31-07-2021 16 1   Download

Deep neural networks (DNN) are a particular case of artificial neural networks (ANN) composed by multiple hidden layers, and have recently gained attention in genome-enabled prediction of complex traits. Yet, few studies in genome-enabled prediction have assessed the performance of DNN compared to traditional regression models.

13p vijeeni2711 30-06-2021 8 1   Download

Blockage of some ion channels and in particular, the hERG (human Ether-a’-go-go-Related Gene) cardiac potassium channel delays cardiac repolarization and can induce arrhythmia. In some cases it leads to a potentially life-threatening arrhythmia known as Torsade de Pointes (TdP).

10p viconnecticut2711 29-10-2020 13 0   Download

Synapse based on two successive memristors builds the synaptic weights of the artificial neural network for training three-bit parity problem and five-character recognition.

16p vivalletta2711 11-01-2020 17 1   Download

Highly tensile manganese steel is in great demand owing to its high tensile strength under shock loads. All workpieces are produced through casting, because it is highly difficult to machine. The probabilistic aspects of its casting, its variable composition, and the different casting techniques must all be considered for the optimisation of its mechanical properties. A hybrid strategy is therefore proposed which combines decision trees and artificial neural networks (ANNs) for accurate and reliable prediction models for ore crushing plate lifetimes.

12p caygaocaolon1 13-11-2019 20 0   Download

In this study, the void fraction percentage was estimated precisely, independent of the flow regime in gaseliquid two-phase flows by using g-ray attenuation and a multilayer perceptron neural network. In all previous studies that implemented a multibeam g-ray attenuation technique to determine void fraction independent of the flow regime in two-phase flows, three or more detectors were used while in this study just two NaI detectors were used.

8p minhxaminhyeu5 30-06-2019 47 2   Download

In this paper we’ll consider only the two-phase short-circuit fault type on a three-phase transmission line. The model use a transmission line at 220kV, 200 km long, frequency at 50Hz with different positions of the failure and different failure short-circuit resistances to test the proposed solutions.

7p doctorstrange1 15-06-2018 34 1   Download

A comprehensive introduction to the most popular class of neural network, the multilayer perceptron, showing how it can be used for system identification and control. The book provides readers with a sufficient theoretical background to understand the characteristics of different methods, and to be aware of the pit-falls so as to make the correct decisions in all situations. This is a very application-oriented text that gives detailed and pragmatic recommendations to guide users through the plethora of methods suggested in the literature.

38p o0_mrduong_0o 30-03-2013 75 13   Download

CHAOTIC DYNAMICS Gaurav S. Patel Department of Electrical and Computer Engineering, McMaster University, Hamilton, Ontario, Canada Simon Haykin Communications Research Laboratory, McMaster University, Hamilton, Ontario, Canada (haykin@mcmaster.ca) 4.1 INTRODUCTION In this chapter, we consider another application of the extended Kalman filter recurrent multilayer perceptron (EKF-RMLP) scheme: the modeling of a chaotic time series or one that could be potentially chaotic. The generation of a chaotic process is governed by a coupled set of nonlinear differential or difference equations.

40p khinhkha 29-07-2010 88 10   Download

LEARNING SHAPE AND MOTION FROM IMAGE SEQUENCES Gaurav S. Patel Department of Electrical and Computer Engineering, McMaster University, Hamilton, Ontario, Canada Sue Becker and Ron Racine Department of Psychology, McMaster University, Hamilton, Ontario, Canada (beckers@mcmaster.ca) 3.1 INTRODUCTION In Chapter 2, Puskorius and Feldkamp described a procedure for the supervised training of a recurrent multilayer perceptron – the nodedecoupled extended Kalman filter (NDEKF) algorithm. We now use this model to deal with high-dimensional signals: moving visual images.

13p khinhkha 29-07-2010 111 7   Download

In this chapter, we consider another application of the extended Kalman filter recurrent multilayer perceptron (EKF-RMLP) scheme: the modeling of a chaotic time series or one that could be potentially chaotic. The generation of a chaotic process is governed by a coupled set of nonlinear differential or difference equations.

40p duongph05 07-06-2010 78 14   Download

In Chapter 2, Puskorius and Feldkamp described a procedure for the supervised training of a recurrent multilayer perceptron – the nodedecoupled extended Kalman filter (NDEKF) algorithm. We now use this model to deal with high-dimensional signals: moving visual images. Many complexities arise in visual processing that are not present in onedimensional prediction problems: the scene may be cluttered with backKalman Filtering and Neural Network

13p duongph05 07-06-2010 79 14   Download