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6 results for “Stochastic Neural Network”
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Research ArticleOpen accessEvery word in the titleConvolution Neural Networks of Dynamically Sized Filters with Modified Stochastic Gradient Descent Optimizer for Sound ClassificationManu Pratap Singh, Pratibha RashmiDeep Neural Networks (DNNs), specifically Convolution Neural Networks (CNNs) are found well suited to address the problem of sound classification due to their ability to capture the pattern of time and frequency domain. Mostly the convolutional neural networks are trained and tested with time-frequency patches of sound samples in the form of 2D pattern vectors. Generally, existing pre-trained convolutional neural … …Journal of Computer Science, Vol. 20, Issue 1 · 13 Dec 2023 · 5,781 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEfficient Implementation of Stochastic Computing Based Deep Neural Network on Low Cost Hardware with Saturation ArithmeticSunny Bodiwala, Nirali NanavatiThis study presents an efficient and rapid implementation of Stochastic Computing (SC) based Deep Neural Network (DNN) on a low-cost hardware platform. The proposed technique uses bipolar signal encoding in stochastic computing which relatively gives low hardware footprint compared to binary computing. Thereinafter, stochastic max function is presented and subsequently used to approximate the hyperbolic tangent activation function in SC. … …Journal of Computer Science, Vol. 16, Issue 11 · 17 Nov 2020 · 6,875 accessesView PDFCite
Research ArticleOpen accessIn the keywordsProcess Physics: Emergent Unified Dynamical 3-Space, Quantum and Gravity: A ReviewReginald Thomas CahillExperiments have repeatedly revealed the existence of a dynamical structured fractal 3-space, with a speed relative to the Earth of some 500 km sec-1 from a southerly direction. Experiments have ranged from optical light speed anisotropy interferometers to zener diode quantum detectors. This dynamical space has been missing from theories from the beginning of physics. This dynamical space generates a … …Physics International, Vol. 6, Issue 2 · 4 Aug 2015 · 8,515 accessesView PDFCite
Research ArticleOpen accessIn the abstractTAGN-IDC: Implicit Discrete Constraints for Tsunami Aware Graph Neural Networks in Spatial Evacuation RoutingSularno, Wendi Boy, Putri Anggraini et al.Tsunami evacuation route requires rapid identification of safe evacuation paths under dynamically changing hazard conditions. A major challenge is incorporating hard binary road-blockage constraints caused by tsunami inundation while maintaining end-to-end differentiability for deep learning models. Existing approaches commonly rely on continuous relaxations or stochastic sampling techniques, which either compromise physical feasibility or increase computational complexity. This study proposes the … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 704 accessesView PDFCite
Research ArticleOpen accessIn the abstractAsymptotic Behavior of an Artificial Neural Network Defined on Multipartite Directed GraphN. C. Majee, A. B. RoyProblem statement: Artificial Neural Network (ANN) are simple models to mimic some essential features of the complex central nervous system. ANN models are realistic due to their inherent stochastic nature of neural computation and strong synchronicity. Different ANN models are associated with directed and signed graphs. The present study proceeded by relaxing certain simplifying assumptions in the ANN model. Approach: … …OnLine Journal of Biological Sciences, Vol. 10, Issue 1 · 30 Jun 2010 · 7,476 accessesView PDFCite