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back propagation through time

Learning Dynamic Generator Model by Alternating Back-Propagation through Time

Learning Dynamic Generator Model by Alternating Back-Propagation through Time

... The main contribution of this paper lies in the combination of the dynamic generator model and the alternating back- propagation through time algorithm. Both the model and al- gorithm are ...

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Speech Recognition using the Epochwise Back Propagation through Time Algorithm

Speech Recognition using the Epochwise Back Propagation through Time Algorithm

... paper, Back propagation neural network architecture used to recognize the time varying input data, and provides better accurate results for the English Alphabet speech ...Epochwise Back ...

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A REAL TIME QRS DETECTION SYSTEM USED ERROR BACK PROPAGATION NEURAL NETWORK

A REAL TIME QRS DETECTION SYSTEM USED ERROR BACK PROPAGATION NEURAL NETWORK

... Error Back Propagation Neural Network (EBP-NN) algorithm for QRS complex locations is ...a Back propagation neural ...of time accuracy and ...of back propagation neural ...

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Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification

Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification

... the back propagation through time approach approximating the time evolution of a recur- rent neural network as a sequence of static networks using gradient ...standard back ...

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Moisture Prediction in Maize Using Three Term Back Propagation Neural Network

Moisture Prediction in Maize Using Three Term Back Propagation Neural Network

... drying time and drying temperature, represents weight from input to hidden node, represents weight from hidden unit to output node and represents output signal from the output node ...

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Improving the Power Quality Based On VSC DSTATCOM with Back Propagation Algorithm through Neural Network

Improving the Power Quality Based On VSC DSTATCOM with Back Propagation Algorithm through Neural Network

... response time, require less space as bulky passive components are eliminated and can be interface with real power sources such as battery, fuel cell ...tolerance through redundant information are major ...

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Secure Cloud Computing Environment against
          DDOS and EDOS Attacks

Secure Cloud Computing Environment against DDOS and EDOS Attacks

... Trace Back through proposed Cloud Trace Back (CTB) to find the source of real attacks, and introduce the use of a back propagation neutral network, called Cloud Protector, Economic ...

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Optimizing Back-Propagation using PSO_Hill and PSO_A*

Optimizing Back-Propagation using PSO_Hill and PSO_A*

... Particle Swarm Optimization (PSO): Particle Swarm Optimization (PSO) is a swarm-based intelligence algorithm [6] influenced by the social behavior of animals such as a flock of birds finding a food source or a school of ...

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Optimized Face Recognition Technique based on PCA and RBF Neural Network

Optimized Face Recognition Technique based on PCA and RBF Neural Network

... training time for both the techniques, neural network using Back Propagation algorithm and the proposed approach using optimized RBF neural network with gradient descent activation ...training ...

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A Novel Cancer Gene Search Model and Classification Using GPSO-BPNN

A Novel Cancer Gene Search Model and Classification Using GPSO-BPNN

... conducted through the info mining algorithms and enforced Geometric Particle Swarm optimization (GPSO) with Back propagation Neural Network (BPNN) for cancer factor search and classification, and the ...

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Medical Image Security Using Watermarking In Back Propagation Neural Network

Medical Image Security Using Watermarking In Back Propagation Neural Network

... of time and resources, depending on the resolution ...computation time and resources ...in time, then the wavelet series of the discrete-time signal is called the ...

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Hole Cleaning Prediction in Foam Drilling Using Artificial Neural Network and Multiple Linear Regression

Hole Cleaning Prediction in Foam Drilling Using Artificial Neural Network and Multiple Linear Regression

... same time, their densities are usually less than one- half of ...flow through a horizontal annuli using back propagation neural network (BPNN) from affecting parameters on cuttings ...

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Bat BP: a new bat based back propagation algorithm for efficient data classification

Bat BP: a new bat based back propagation algorithm for efficient data classification

... training time of the ...colony back-propagation (ABC- BP) algorithm [11-12], genetic algorithm (GA) [13], hybrid PSO-BP [14], and evolutionary artificial neural networks algorithm (EA) ...Bat-Based ...

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Back Propagation SIFT using Fuzzy Logic

Back Propagation SIFT using Fuzzy Logic

... With the explosive enhancement in multimedia technology large amount of dataset is available on internet.So the process of retrieving required image from this huge dataset is main task in computer vision. There are ...

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The tuning of error signal for back-propagation algorithms

The tuning of error signal for back-propagation algorithms

... Grid computing means a multiple independent computing, because it is composed of resource nodes not located within a single administrative domain. The goal of grid is to only provide secure grid service resources to ...

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The effect of adaptive parameters on the performance of back propagation

The effect of adaptive parameters on the performance of back propagation

... The concept of ANN approach began in 1943 when McCulloch and Pits introduced the first mathematical model of a biological neuron (McCulloch & Pitts, 1943). At that time, the significance of this model was its ...

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A Novel Approach of Handwritten Devanagari Character Recognition through Feed Forward Back Propagation Neural Network

A Novel Approach of Handwritten Devanagari Character Recognition through Feed Forward Back Propagation Neural Network

... India is a multi-lingual and multi-script country. Devanagari scripts are originated from Brahmi script through various transformations. It was originally developed to write Sanskrit but was later used to write ...

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Diabetic prediction using fuzzy back propagation and analysis

Diabetic prediction using fuzzy back propagation and analysis

... fuzzy back propagation using triangular membership function and naive Bayesian are all implemented in JDK ...fuzzy back propagation results have been obtained using variation of ...

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How Ties to Professional Support Networks Impact Social Outcomes among Homeless Youth

How Ties to Professional Support Networks Impact Social Outcomes among Homeless Youth

... goal, time, min_grad, srchFcn, max_fail, scal_tol, gama, alpha, beta, delta, up_lim, low_lim, maxstep, minstep, and ...goal, time, max_fail, min_grad and ...

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Unleashing Power of Artificial Intelligence for Network Intrusion Detection Problem

Unleashing Power of Artificial Intelligence for Network Intrusion Detection Problem

... The power of a neural network stems from the combination of many units in a network. A certain network can be tuned to solve a specific problem by varying the connection topology and values of the connecting weights ...

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