... input layer was 96 2 .1. 1 Character database acquisition 3 .1 Auto-associator (AA) feature extractor The training and test characters/words used in this research came from the following directories ... MLP and AA and test characters were the same as those of MLP and AA as well But the number of classes of each network was only rather than 24 The number of iterations for all networks was 5000 As ... Classification rates for the AA The comparison of performance between the AA and the MLP was the major aim of this research The results in Table (rows 1, 2,3,4) were obtained by training the AA...
... Therefore, for on-line updating of Artificial neuralnetwork based adaptive controller for DC motors 28 Chapter ANN based Adaptive Controller weights and biases of the ANN, an adaptive learning rate ... weights and biases according to equations (3.4)-(3 .10 ) Figure 3.3 Flowchart for adaptive learning rate η Artificial neuralnetwork based adaptive controller for DC motors 29 Chapter ANN based Adaptive ... to be estimated Artificial neuralnetwork based adaptive controller for DC motors 18 Chapter Theoretical Development 2.5 ANN Structure for the Controller 2.5 .1 Feedforward neuralnetwork structure...
... Tcr Tij partial cross correlation between user i and user j normalized cross correlation matrix information data rate k th user’s transmitted spread spectrum signal covariance matrix in Mahalanobis ... TDMA Additive White Gaussian Noise Annealed NeuralNetwork Annealed NeuralNetwork Multiuser Detector Bit Error Rate Binary Phase Shift Keying Conventional Detector Code Division Multiple Access ... NeuralNetwork (HNN), multistage detector (MS -10 ) and annealed neuralnetwork (ANNMD) We also use the optimum multiuser detector (OMD) as comparison benchmark for all the MUDs To have broader...
... Those features are used as the input of aneuralnetworkfor training based on the back-propagation algorithm forneural networks After the neuralnetwork is well trained, new input data will ... obtain important features of candidate text regions As a practical example, a gray-level original image is shown in Figure The corresponding DWT sub-bands are shown in Figure We can extract features ... segmentation,” IEEE International Conference on Neural Networks, 19 96 , Volume: 3, 3-6 June 19 96 Page(s): 16 64 -16 69 vol.3 [4] Yu Zhong, Hongjiang Zhang, Jain, A. K., ” Automatic caption localization in compressed...
... larger than the average accordingly The next three are the standard errors of number of pixels for all colors; colors smaller than the average color and colors larger than the average color Basically ... two basic spatial features, i.e., width and height, there are totally 14 features used for the neuralnetwork analysis D Contours classification using neuralnetwork We extract the above features ... used here are greyscale name card images, for color or other types of images, the method can still be applied because color images can be transformed to gray scale easily or we can just try to...
... creation of a complete database for the input and output data for the training and validation of the networkfor each system characteristics The input data come from HPS (e.g pump power, available ... Genetic Algorithms) to analyse cases of daily operation in water supply systems with complementary renewable energy sources [3] 2.4 Artificial neural networks Artificial neural networks (ANN) have ... controllable factors that affect the algorithm’s rate of learning The two factors are the learning rate coefficient (eta), and the momentum factor, alpha To optimize the rate at which anetwork learns,...
... linear huấn luyện đến hàm gần với số kết nối cố định 1. 5 MÔ HÌNH BACKPROPAGATION NETWORK1. 5 .1 Hoạt động mạng Backpropagation Mô hình NeuralNetwork bao gồm nhiều dạng mạng khác Perception, Radial ... bé tuyến tính Mô hình NeuralNetwork với lớp ẩn giống với mô hình hồi quy phi tuyến Backpropagation network loại NeuralNetwork feed-forward với quy tắc giám sát Feed-forwad đề cập đến hướng dòng ... thống thường sử dụng MATLAB Hiện nay, phần mềm phổ biến thiết kế dùng cho mô hình NeuralNetwork gồm có Alyuda NeuroIntelligence, Stuttgart NeuralNetwork Simulator, Emergen, JavaNNS NeuroSolutions...
... ngưỡng tạo ngõ n n = w1,1p1 + w1,2,p2 + ……w1,R pR + b hay n = W*p + b Nếu có nhiều neuron cách biểu diễn không hiệu quả, đònh ngh a lớp gồm nhiều neuron sau 1. 2 Cấu trúc mạng Hai hay nhiều neuron kết ... nhiều hàm truyền áp dụng Neural Networks, ba hàm thường sử dụng Hard Limit, Linear, Log-Sigmoid Tổng quát với hàm truyền có đầu vào một nhóm vector đầu a = f ( p * w + b ) Với a : đầu p : đầu vào ... linear huấn luyện đến hàm gần với số kết nối cố đònh CẤU TRÚC DỮ LIỆU Cấu trúc đònh dạng liệu vào ảnh hưởng đến việc mô mạng Có hai loại mạng static network dynamic network Hai kiểu vector đầu...
... classification is perhaps the most important application of artificial neural networks In fact, a majority of neuralnetwork applications can be categorized as solving complex pattern classification problems ... networks disagree: ensemble methodforneural networks, in Neural Networks for Speeach and Image Processing, R .J Mammone, Ed., Chapman & Hall, Boca Raton, FL, 19 93 [10 ] A Krogh and J Vedelsby, Neural ... linear signal processing algorithms Neuralnetwork applications to signal processing are mostly for nonlinear signal processing algorithms Data-adaptive vs data-independent formulation — A data-independent...
... (http://www.sgi.com/tech/mlc/) 1. 2.3 Radial Basis Networks A radial basis network is a feed-forward neuralnetwork using the radial basis activation function A radial basis function has the general form of f (||x ... error back-propagation formula, the back-propagation training algorithm for MLP can be summarized below in the MATLAB m-file format: Algorithm Listing: Back-Propagation Training Algorithm for ... Systems Paisarn Muneesawang, Hau-San Wong, Jose Lay, and Ling Guan 12 Applications of Neural Networks to Image Processing and Huai Li 13 Hierarchical Fuzzy Neural Networks for Pattern Classification...
... began to apply neural networks for group technology (GT) applications in the late 19 80s and early 19 90s After a decade of effort, neural networks have emerged as an important and viable means for ... Jamal [19 93] Malave & Ramachandran [19 91] Venugopal & Narendran [19 9 2a, 19 94] Chu [19 93] Malakooti & Tang [19 95] Moon [19 9 0a, 19 90b] Moon & Chi [19 92] Currie [19 92] Lee et al [19 92] Kiang, Hamu ... Zhang and Huang [19 95] fora review of artificial neural networks for other, closely related areas in manufacturing References Arizono, I., Kato, M., Yamamoto, A and Ohta, H., 19 96, Anew stochastic...
... of a back-propagation neuralnetworkfor manufacturing process parameters, Journal of Intelligent Manufacturing, 2, 15 5, 19 91 61 Sathyanaryanan, G., Lin, I J. , and Chen, M K., Neural networks and ... technology: Aneuralnetwork approach, International Journal of Production Research, 30, 13 53, 19 92 19 Liao, T W., and Chen, L J. , An evaluation of ART -1 neural networks for GT part family and machine ... human operators perform the classification tasks Jamal [40] also applied a multilayer feedforward neuralnetwork trained with the BP algorithm for grouping part families and machine cells for a...
... signals are compared with the output of a single UP/DOWN counter and processed through a logic block to generate the PWM outputs forforforforfor (5) forforforforforforforforforfor ... only IV PERFORMANCE EVALUATION Fig Segmentation of neuralnetwork output for U -phase P states and performed with the and signals only Similar operations are signals of all the phases and all the ... corresponding and from the figure The remaining time interval in aphase corresponds to zero state as indicated Equations (3) and (4) can be expressed in the general form forforfor - (9) for (3) for for...
... machining, ASME Trans J Engineering for Industry, vol 11 2, pp 12 2 -13 1 Grabec, I., and Kuljanic, E 19 94 Characterization of manufacturing processes based upon acoustic emission analysis by neural networks, ... wi° assigned to each node represents the information gain-weighted value, which is learned based on information available at the signal/index evaluation stage The information gains can always ... been applied to solder joint inspection due to learning capability and nonlinear classification performance Among many neuralnetwork approaches, the LVQ neuralnetwork classifier [Kim and Cho, 19 95]...
... S a 40 S a 50 S a 60 a1 1a 21 a 31 a 41 a 51 a 61 a1 2 a 22 a 32 a 42 a 52 a 62 F1 b10 a1 3 a 23 F2 b20 1nv a 33 and F3 ... Wear Monitoring with Wavelet Packet Transform-Fuzzy Clustering Method, ” Wear, 19 98, 219 (2), 14 5 15 4.) 15 .3 Wavelet Transforms 15 .3 .1 Wavelet Transforms (WT) An energy limited signal f(t) can ... Figure 15 . 21 The results showed that the above method had a more accurate estimation of tool wear states 15 .6 Tool Wear Monitoring with Wavelet Transforms and Fuzzy NeuralNetwork Flexible manufacturing...