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Housing price prediction using neural networks
Published 2016“…There are more than 40 different kinds of neural network models, the most common ones are Multilayer Perceptron (MLP), Hopfield net, Boltzmann Machine, Backpropagation (BP) net, etc. …”
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Final Year Project (FYP) -
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Solar PV parameter forecast using generalized neural networks
Published 2023Get full text
Final Year Project (FYP) -
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Associative memories via predictive coding
Published 2021“…In an extensive comparison, we show that this new model outperforms in retrieval accuracy and robustness popular associative memory models, such as autoencoders trained via backpropagation, and modern Hopfield networks. In particular, in completing partial data points, our model achieves remarkable results on natural image datasets, such as ImageNet, with a surprisingly high accuracy, even when only a tiny fraction of pixels of the original images is presented. …”
Conference item -
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Quantum theory of a resonant photonic crystal
Published 2013Get full text
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Journal Article -
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Quadratic Programming for TDMA Scheduling in Wireless Sensor Networks
Published 2011-09-01“…Schedule optimization is transformed into a quadratic programming (QP) task, which is then solved by the Hopfield net in polynomial time. In this way, an energy efficient scheduling can be obtained which meets a given delay requirement in TDMA systems. …”
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Article -
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Bridging ribosomal synthesis to cell growth through the lens of kinetics
Published 2023Get full text
Journal Article -
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Stochastic neural networks
Published 1991-12-01“…Given the explosivo amount of material, only models bearing a stochastic component in the function or analysis are presented, such as Hopfield and feedforward nets, Boltzman machines and some recurrent networks. …”
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Credit evaluation of electricity sales companies based on an enhanced DHNN model
Published 2024-01-01Get full text
Article -
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A NOVEL APPROACH TO SUPER RESOLUTION MAPPING OF MULTISPECTRAL IMAGERY BASED ON PIXEL SWAPPING TECHNIQUE
Published 2012-07-01Get full text
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Mathematical modeling and simulation of stem cell differentiation and reprogramming by Waddington's epigenetic landscape
Published 2018“…Here, we proposed a data-driven method, named HopLand, to model the process of stem cell fate determination by using the continuous Hopfield Network (CHN) to map cells in a Waddington’s epigenetic land- scape. …”
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Single-row mapping and transformation of connected graphs
Published 2007“…The intervals are then mapped into a network of non-crossing nets using our previously developed tool called ESSR. …”
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On the analysis of ''simple'' 2D stochastic cellular automata
Published 2010-01-01“…This paper analyzes the dynamics of a two-dimensional cellular automaton, 2D Minority, for the Moore neighborhood (eight closest neighbors of each cell) under fully asynchronous dynamics (where one single random cell updates at each time step). 2D Minority may appear as a simple rule, but It is known from the experience of Ising models and Hopfield nets that 2D models with negative feedback are hard to study. …”
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