steepest descent gradient algorithm
Accelerated Mann and CQ algorithms for finding a fixed point of a nonexpansive mapping
... Picard algorithm to the smooth convex minimization problem and point out that the Picard algorithm is the steepest descent method for solving the minimization ...Picard algorithm by ...
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Adaptive Filtering using Steepest Descent and LMS Algorithm
... an algorithm which is capable of separating this noise from the desired response called as the adaptive filtering ...recursive algorithm continuously to adjust its tap weights for operation in an unknown ...
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HANDWRITTEN NUMERAL PATTERN RECOGNITION TECHNIQUES: REVIEW PAPER
... use steepest descent to train a multilayer network with sigmoid functions, because the gradient can have a very small magnitude and, therefore, cause small changes in the weights and biases, even ...
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The effect of adaptive gain and adaptive momentum in improving training time of Gradient Descent back propagation algorithm on classification problems
... propagation algorithm based on extrapolation of each individual interconnection ...propagation algorithm is individually ...conjugate gradient algorithm could be used to train multilayer feed ...
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Detection of Mobile Keyloggers Using Deep Learning
... Gradient descent is an algorithm of first order iterative optimization to find the minimum of a ...as steepest descent ...function's gradient with respect to the parameters where ...
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1. First and second order training algorithms for artificial neural networks to detect the cardiac state
... the steepest descent algorithm is based on first order Taylor’s series expansion, whereas the conjugate gradient algorithm is based on the second order Taylor’s ...order ...
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An Improved Gauss Newtons Method based Back propagation Algorithm for Fast Convergence
... The steepest descent back-propagation (SDBP) is used in several applications despite its asymptotic slow convergence rate ...The algorithm is also known as a gradient ...of steepest ...
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The Effect of Adaptive Gain and Adaptive Momentum in Improving Training Time of Gradient Descent Back Propagation Algorithm on Classification Problems
... propagation algorithm based on extrapolation of each individual interconnection ...propagation algorithm is individually ...conjugate gradient algorithm could be used to train multilayer feed ...
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Optimal Control of Microgrid Networks Using Gradient Descent and Differential Evolution Methods
... are Steepest Descent method, Newton method and Differential Evolution ...of gradient descent methods where as the differential evolution is an Evolutionary ...The gradient ...
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The hybrid steepest descent method for solutions of equilibrium problems and other problems in fixed point theory
... the gradient projection algorithm and the hybrid steepest descent method and prove the strong convergence to a common element of the equilibrium problem; the null space of an inverse strongly ...
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An Efficient Algorithm to Analyse the Cost Sensitive Measures on Datasets
... efficient algorithm to analyse the cost sensitive measure is ...sensitive gradient descent algorithm and constraint based gravitational search algorithm is ...proposed algorithm ...
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Optimal Parameter Selection Using Three-term Back Propagation Algorithm for Data Classification
... (BP) algorithm is a well-known technique used in the implementation of artificial neural ...BP algorithm had gained attention to many researchers and been implemented in diverse disciplines and ...BP ...
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Multi Valued Neuron with Sigmoid Activation Function for Pattern Classification
... In this paper, we propose a new neuron model, MVN-sig, to simulate the mechanism of MVN with dif- ferentiable activation function. We consider the activation function of MVN as a function of the argument of a weighted ...
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Mann type hybrid steepest descent method for three nonlinear problems
... iterative algorithm is based on Korpelevich’s extragradient method, the viscosity approximation method [], Mann’s it- eration method, and the hybrid steepest-descent ...erative algorithm ...
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Active noise reduction in double panel structures : decentralized adaptive feedforward control
... 3.4.1 Effect of plant uncertainties As was shown in equation 32 , a steepest descent algorithm with effort weighting can be used to control the system to a minimum error solution when t[r] ...
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An Iterative Algorithm for Generalized Mixed Equilibria with Variational Inequalities
... hybrid steepest-descent method for the variational inequality problems over the inter- section of the fixed-point sets of nonexpansive map- pings, in: Inherently Parallel Algorithms in Feasi- bility and ...
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Certain Systems Arising In Stochastic Gradient Descent
... 2. Kesten algorithm [Kes58] introduced a stochastic approximation process in hopes of accelerating the convergence of the Robbins-Monro algorithm [RM51]. The idea here is: when we are confident that the ...
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Analysis Of Line To Ground Fault In Transformer By Elman’S Network Using Gradient Descent Back Propagation Algorithm
... Inrush current is really caused by saturation of the magnetic core of the transformer during part of the power cycle,therefore its waveform has distinct gap characteristics.when a transformer internal fault occurs, the ...
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Combining dual-tree complex wavelets and multiresolution in iterative CT reconstruction with application to metal artifact reduction
... In this work, we showed how DT-CWT can be applied in the tomographic reconstruc- tion process via a multiresolution (coarse-to-fine) version of a classical TV regularization algorithm. The numerical experiments ...
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New Programming Approach for Steepest Descent Optimization of Rocket Trajectories
... [7]Siddal, J.N.,“ Optimal Engineering Design: Principles and Applications”, Mercell Dekker Inc., New York, NY, 1982. [8]Bryson, A. E. and Denham, W. F., “A Steepest-Ascent Method for Solving Optimum Programming ...
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