Neural network toolbox

This tutorial uses the MATLAB Control System Toolbox, the Fuzzy Logie Toolbox and the Neural Network Toolbox. Problems in Chapter 10 are used as design examples. 

The MATLAB Neural Network Toolbox This Toolbox was not used in the Examples given in Chapter 10. For details on the Toolbox, type... 

Demuth, H. and Beale, M. (1993) Neural Network Toolbox for Use with MATLAB - User s Guide, The MathWorks, Inc., Natick, Mass. 

H. Demuth and M. Beale, Neural Network Toolbox User s Guide, Version 4, Mathworks Inc., Natick, MA, 2002. 

Usually complex structures with more than 15 layers are employed, called the multilayer perceptron (MLP). Some of the commercial programs which have been used to fit tableting parameters are INForm (Intelligensys, Billingham Teesside), CAD/Chem (AI Ware, Cleveland, OH), which is no longer commercially available, and the Neural Network Toolbox of MATLAB (MathWorks, Natick, MA). 

The regression models, cross-validation cycles and statistical analyses were ptrogrammed using the MATLAB Release 12 software package. The neural network toolbox available in this package was used for the training of the multilayer perceptron neural networks. 

Demuth, H., Beale, M. Hagan, M. 2004. Neural Network Toolbox for use with Matlab. User s guide. Ver.4. http //courses.washington.edu/css485/nnet.pdf... 

IBM SPSS is a comprehensive, easy-to-use set of data and predictive analytics tools for business users, analysts and statistical programmers [45]. Its package has a neural network toolbox which includes both Multilayer Perceptron (MLP)-type [46] as well as RBF-type [47] models. Provisions for random number generation (seed) are also provided with this software under the Transformations option. Any data set for neural network modelling purpose has to be partitioned into three partitions ... 

The first example to be considered is a static function approximation. The MATLAB neural network toolbox (Mathworks, 2006) will be used. A two-layer feed-forward neural network, consisting of a hidden layer and output layer, will be trained to approximate the sum of two sine waves. The function can be described by ... 

The Mathworks, Description of the neural network toolbox http //www.mathwoiks.com/pioducts/neuralnet/. 

A fast back propagation training algorithm can be used which is available in the Neural Network Toolbox in MATLAB. 

An ANN was developed as an aid in understanding the relationship among the different parameters or features of a generic type of vessel, such as vessel s size, age, degree of machinery redundancy, external factors, etc. Once this relationship is understood, it could be used in predicting vessel failure. A fast back-propagation ANN in the Neural Network toolbox... 

Demuth H, Beale M, Hagan M (2008) Neural Network Toolbox 6 User s Guide Matlab... 

To demonstrate how the Toolbox is used, eonsider a neural network with a strueture shown in Figure A1.9. 

M. Norgaard, Neural network based system identification toolbox. Technical report. Institute of Automation, Technical University, Denmark, 1995. 

For the purpose of comparison, optimisation using a single neural network was first carried out. Table 2 shows the obtained results. As can be seen from the table, the values for the difference between the final amounts of product and by-product using the PSO codes were similar to the ones obtained using the MATLAB Optimisation Toolbox function,yJwzwcow, in this fed-batch reactor. However, PSO can cope with multiple local minima in general as shown in Section 2. 

Abstract. Artificial neural networks (ANN) are useful components in today s data analysis toolbox. They were initially inspired by the brain but are today accepted to be quite different from it. ANN typically lack scalability and mostly rely on supervised learning, both of which are biologically implausible features. Here we describe and evaluate a novel cortex-inspired hybrid algorithm. It is found to perform on par with a Support Vector Machine (SVM) in classification of activation patterns from the rat olfactory bulb. On-line unsupervised learning is shown to provide significant tolerance to sensor drift, an important property of algorithms used to analyze chemo-sensor data. Scalability of the approach is illustrated on the MNIST dataset of handwritten digits. 

Mathematical modeling. SIMULINK for simulating nonlinear dynamic systems. Toolboxes for symbolic math, neural networks, statistics, spline analysis, signal processing, and image processing. PCs (Windows) and Macintosh. 

An effective way to reduce the number the number of inputs is to transform the input space of mutually dependent variables into a space of independent variables by principal component analysis (PCA). This space is usually much smaller. This transformation forms the basis of the construction of partial least square (PLS) models. Also in many packages for neural-network design a PCA toolbox is present. 

Next, a neural network OE model will be developed. The neural network identification toolbox (Norgaard, 2000) is used. It will be assumed that ... 

For advanced techniques in modeling, identification, and control, MATLAB has a variety of additional toolboxes that are licensed individually. Relevant toolboxes for process control include control system, fuzzy logic, system identification, model predictive control, neural networks, optimization, partial differential equations, robust control, and statistics. 

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