17 papers · ranked by Valyu relevance
Bryant, Dustin, Jim Woodcock, Simon J. Foster
This paper presents a formalized analysis of the sigmoid function and a fully mechanized proof of the Universal Approximation Theorem (UAT) in Isabelle/HOL, a higher-order logic theorem prover. The sigmoid function plays a fundamental role in neural networks; yet, its formal properties, such as differentiability…
Savadam Balaji, K. Baskaran
Prediction of annual rice production in all the 31 districts of Tamilnadu is an important decision for the Governmentof Tamilnadu.Rice production is a complex process and non linear problem involving soil, crop, weather,pest, disease,capital, labour and management parameters. ANNsoftware wasdesignedand developedwith…
Ugoline Godeau, Christophe Bouget, Jérémy Piffady, Tiffani Pozzi + 1 more
'Frédéric Gosselin'] Title: Abstract Defining mathematical terms and objects is a constant issue in ecology; often definitions are absent, erroneous, or imprecise. Through a bibliographic prospection, we show that this problem appears in macro-ecology (biogeography and community ecology) where the lack of definition…
Siqiu Xu, Xi Li, Chenchen Xie, Houpeng Chen + 3 more
'Zhitang Song' 'Jung Ho Yoon'] Computing-In-Memory (CIM), based on non-von Neumann architecture, has lately received significant attention due to its lower overhead in delay and higher energy efficiency in convolutional and fully-connected neural network computing. Growing works have given the priority to researching…
Andreas Skiadopoulos, Maria Knikou
Recruitment input-output curves of transspinal evoked potentials that represent the net spinal motor output of alpha motor neurons, and those of cortically, spinally or peripherally induced responses are used extensively in research as neurophysiological biomarkers to establish physiological or pathological behavior of…
Paul Barry
Sigmoid functions play an important role in many areas of applied mathematics, including machine learning, population dynamics and probability. We place the study of sigmoid functions in the context of the derivative sub-group of the group of exponential Riordan arrays. Links to families of polynomials are drawn, and…
Jean Daunizeau
This note is concerned with accurate and computationally efficient approximations of moments of Gaussian random variables passed through sigmoid or softmax mappings. By definition, a sigmoid function is real-valued and differentiable, having a non-negative first derivative which is bell shaped (Han and Moraga, 1995).…
Lisa Buche, Lauren G. Shoemaker, Lauren M. Hallett, Peter Vesk + 2 more
The ability of species to form diverse communities is not fully understood. Species are known to interact in various ways with their neighborhood. Despite this, common models of species coexistence assume that per capita interactions are constant and competitive, even as the environment changes. In this study, we…
Changsoo Shin
Modern AI systems excel at pattern recognition and task execution, but they often fall short of replicating the layered, self-referential structure of human thought that unfolds over time. In this paper, we present a mathematically grounded and conceptually simple framework based on smoothed step functions-sigmoid…
Abdourrahmane M. Atto, Sylvie Galichet, Dominique Pastor, Nicolas Méger
'Nicolas Méger'] The paper proposes representation functionals in a dual paradigm where learning jointly concerns both linear convolutional weights and parametric forms of nonlinear activation functions. The nonlinear forms proposed to perform the functional representation are associated with a new class of parametric…
Paulo Sergio Rodrigues, Guilherme Wachs-Lopes, Ricardo Morello Santos, Eduardo Coltri + 1 more
'Eduardo Coltri' 'Gilson Antonio Giraldi'] This paper proposes the q-sigmoid functions, which are variations of the sigmoid expressions and an analysis of their application to the process of enhancing regions of interest in digital images. These new functions are based on the non-extensive Tsallis statistics, arising…
Andrew R Auty
The conventional interpretation^1^ of a logistic curve in biology is that it indicates the presence of an infection-like mechanism bounded by a saturation limit e.g. saturation occurs when the whole population has been infected. However, a logistic form may be generated by the fluctuating approach of biological systems…
Siqi Fang, Paul D.W. Kirk, Marcus Bantscheff, Kathryn S. Lilley + 1 more
The thermal stability of proteins can be altered when they interact with small molecules, other biomolecules or are subject to post-translation modifications. Thus monitoring the thermal stability of proteins under various cellular perturbations can provide insights into protein function, as well as potentially…
Lane Yoder, Sunder Ali Khowaja
The networks proposed here show how neurons can be connected to form flip-flops, the basic building blocks in sequential logic systems. The novel neural flip-flops (NFFs) are explicit, dynamic, and can generate known phenomena of short-term memory. For each network design, all neurons, connections, and types of…
Yusuke Watanabe, Hiroshi Ban, Nobuhiro Hagura, Yuji Ikegaya
A neural network is a machine learning algorithm that can learn and make predictions by adjusting the strength of the connections between nodes. The sigmoid function is commonly used as an activation function in these nodes. This study explores the potential applicability of biological materials in the development of…
Grzegorz Dudek
Randomized methods of neural network learning suffer from a problem with the generation of random parameters as they are difficult to set optimally to obtain a good projection space. The standard method draws the parameters from a fixed interval which is independent of the data scope and activation function type. This…
Purushottam D. Dixit
In modern biological physics, there is a great interest in building generative probabilistic models for ensembles of covarying binary variables. A popular approach is to use the maximum entropy principle. Here, one builds generative models that use as constraints lower level statistics estimated from the data. While…