feed-back and feed-forward
A Novel Approach of Handwritten Devanagari Character Recognition through Feed Forward Back Propagation Neural Network
... Handwritten character recognition plays an important role in the modern world. It can solve more complex problems and makes human’s job easier. The present paper portrays a novel approach in recognizing handwritten ...
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A Novel Stream Cipher on Feed forward Model
... different feed-forward models, such as guess and decision attack, fast correlation attack and algebraic attacks ...the feed-forward model in ...novel feed-forward model based on ...
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A feed forward spinal cord glycinergic neural circuit gates mechanical allodynia
... a feed-forward inhibitory circuit located at the junction of spinal laminae II/III, but, strikingly, this feed-forward inhibition is abrogated after peripheral nerve injury or glycine ...
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Design of a Novel Feed forward Model
... Abstract. Feed-forward model is a basic pseudo random sequence generator (PRSG) using in stream ...A feed-forward model is constructed. Inversion attack on feed-forward model is ...
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Crop Cost Forecasting using Artificial Neural Network with feed forward back propagation method for Mysore Region
... ABSTRACT: In recent days, agriculture crop price examination is emerging as a significant research field. In this scenario, Mysore district (Karnataka) is undertaken for research investigation. One of the major concern ...
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A New and Effective Approach for Fingerprint Recognition by using Feed Forward Back Propagation Neural Network
... Various methods have been used to identify a person through the fingerprint image. In this work to increase the accuracy of the result a new approach have been implemented in which each sample is divided into four parts ...
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Cellular automata simulation of topological effects on the dynamics of feed-forward motifs
... with different architecture, and the relationship between topology and overall process rate in feed-forward loops. A variety of stochastic simulation methods exist that can be used to model networks ...
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Breast Cancer Classification using Feed Forward Back Propagation Neural Network (BPNN) Classifier
... using Feed Forward Back Propagation Neural Network (BPNN) ...using Feed Forward Back Propagation Neural Network classifier has achieved excellent classification accuracy compared ...
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Brain Tumor Detection and Classification with Feed Forward Back Propagation Network
... whenever distinguished at beginning period; it can increase the intracranial pressure which can spoil the brain permanently. Brain tumor symptoms depend upon the size of tumor, location and its type. Its threat levels ...
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Palmprint Biometrics using Feed Forward Back Propagation Neural Network
... Feed forward back propagation neural network are used for training and testing. Training algorithm is Levenberg- Marquardt, performance is measure by mean square error, and data division is random. ...
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CODE CLONE DETECTION USING WEIGHTED FEED FORWARD BACK PROPOGATION NEURAL NETWORK
... nature. Back propagation performs a slope drop within the solution's vector space towards a 'global minimum' along the steepest vector of the mistake ...error. Back propagation is a technique of training ...
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REVIEW STRATEGY FORFACERECOGNITION USING GABOR FILTER
... wavelets& feed forward neural network is ...& feed forward neural network for both finding feature points and extracting feature ...
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Hybrid Techniques for Arabic Letter Recognition
... The used corpus of experimentation is based on all Arabic letters with their four vowels pronounced by four speakers. The main features were extracted by using separately different known techniques in speech analyzing ...
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THIN FILM ROUGHNESS OPTIMIZATION IN THE TIN COATINGS USING GENETIC ALGORITHMS
... This article is organized as follows: Section 2 gives a broad description of feed-forward artificial FFNN Neural Networks, the enhanced bat algorithm EBAT, EBAT for training feed-forward[r] ...
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Prediction of Weld Bead Geometry and Penetration in Electric Arc Welding using Artificial Neural Networks
... The Multi-Layer Perception Neural Network is perhaps the most popular network architecture in use today. The units each perform a biased weighted sum of their inputs and p ass this activation level through an activation ...
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Comparison of artificial neural network and multivariate regression methods in prediction of soil cation exchange capacity (Case study: Ziaran region)
... (feed-forward back propagation network) were employed to develop a pedotransfer function for predicting soil parameter using easily measurable characteristics of clay and organic ...
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Artificial Intelligence in the Estimation of Patch Dimensions of Rectangular Microstrip Antennas
... of back propagation training algorithm of MLFFBP-ANN (Multilayer feed forward back propagation Artificial Neural Network) and RBF-ANN (Radial basis function Artificial Neural Network) has been ...
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Forgetting Factor Nonlinear Functional Analysis for Iterative Learning System with Time-Varying Disturbances and Unknown Uncertain
... This research is organized as follows. Section 2 presents some preliminary knowledge for the nonlinear iterative learning control systems with time-varying disturbances. In Section 3, the feed-forward ILC ...
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Neural Network in Image Compression
... the back propagation is very popular for image compression technique The need for effective data compression is evident in almost all applications where storage and transmission of digital images are ...Multilayer ...
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New Approaches for Image Compression Using Neural Network
... The dimensionality of input feature vector is changed by considering the small eigenvalues as zeros. The accu- racy of the obtained results depends upon the selected threshold value of an eigenvalue. If the threshold ...
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