Perceptron learning in engineering design. Microcomp. Civil Eng. 4, 247 256.Adeli, H., and Yeh, C. (1989). "Perceptron learning in engineering design." Microcomputers in Civil Engineering, 4(4), 247-256.ADELI H and YEH C (1989) Perceptron learning in engineering design. Microcomput. ...
The algorithm used by Perceptron to modify the weights (in other words, to learn) is the following. Perceptron learning rule 1. Initialize the connections with a set of weights generated at random. 2. Select an input vector x¯ from the training set. Let y be the output value returned ...
Learning in MLPs also consists in adjusting its perceptrons' weights so as to provide low error on the training data. This is traditionally done using the backpropagation algorithm [151], which attempts to minimize the MSE. However, other algorithms can also be used. In this chapter, we will...
The training of a multilayer perceptron neural network (MLPNN) concerns the selection of its architecture and the connection weights via the minimization o... WWY Ng - 《IEEE Transactions on Neural Networks & Learning Systems》 被引量: 8发表: 2016年 加载更多来源...
In this paper, a new learning algorithm, called the Modified Recursive Least Square (MRLS), is introduced for the Hybrid Multilayered Perceptron (HMLP) net... MS Al-Batah,NAM Isa,KZ Zamli,... - 《Applied Soft Computing》 被引量: 50发表: 2010年 Multi-classify Hybrid Multilayered Perceptr...
We present nonlinear photonic circuit models for constructing programmable linear transformations and use these to realize a coherent perceptron, i.e., an all-optical linear classifier capable of learning the classification boundary iteratively from training data through a coherent feedback rule. Through ...
Our proposed modified perceptron learning learning is then practical especially when noise exists in the training set or when the requirement of computational time is critical.会议名称: TENCON '91.1991 IEEE Region 10 International Conference on EC3-Energy, Computer, Communication and Control Systems ...
In this letter, an attempt has been made to examine the machine learning [multilayer perceptron (MLP) neural networks and support vector machine (SVM)] ... A Taravat,F Del Frate,C Cornaro,... - 《IEEE Geoscience & Remote Sensing Letters》 被引量: 41发表: 2014年 AN INCREMENTAL FRAMEWORK...
There is little guidance in the literature as to what the learning coefficient η should be; if it is taken too small, convergence to the correct parameters may take an extremely long time. However, if η is made large, learning is much more rapid but the parameters may diverge or oscillat...
Learning strategies are also discussed. The new type of PRBF network and its learning via repeated local optimization is demonstrated on a numerical example together with RBF and MLP for comparison. This paper is organized as follows: Basic properties of MLP and RBF neurons are summarized in the...