Results 31 to 40 of about 127,617 (265)

Gradient Amplification: An Efficient Way to Train Deep Neural Networks

Big Data Mining and Analytics, 2020
Improving performance of deep learning models and reducing their training times are ongoing challenges in deep neural networks. There are several approaches proposed to address these challenges, one of which is to increase the depth of the neural ...
Sunitha Basodi, Chunyan Ji, Haiping Zhang, Yi Pan   +3 more
doaj   +1 more source

Neural network channel estimator for time‐variant frequency‐selective fading channels

Electronics Letters, 2023
The next generations of wireless communications systems are pushing the limits of the channel estimation methods utilized in the orthogonal frequency division multiplexing receptors.
Vinicius Piro Barragam, Fadi Jerji, Cristiano Akamine   +2 more
doaj   +1 more source

Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys

Crystals
This study evaluates the predictive capabilities of various machine learning (ML) algorithms for estimating the hardness of AlCoCrCuFeNi high-entropy alloys (HEAs) based on their compositional variables.
Uma Maheshwera Reddy Paturi, Muhammad Ishtiaq, Pasupuleti Lakshmi Narayana, Anoop Kumar Maurya, Seong-Woo Choi, Nagireddy Gari Subba Reddy   +5 more
doaj   +1 more source

Differences in Sodium Channel Densities in the Apical Dendrites of Pyramidal Cells of the Electrosensory Lateral Line Lobe

Frontiers in Neural Circuits, 2019
Heterogeneity of neural properties within a given neural class is ubiquitous in the nervous system and permits different sub-classes of neurons to specialize for specific purposes.
Sree I. Motipally, Kathryne M. Allen, Daniel K. Williamson, Gary Marsat   +3 more
doaj   +1 more source

Implementation of Modified Backpropagation with Conjugate Gradient as Microarray Data Classifier with Binary Particle Swarm Optimization as Feature Selection for Cancer Detection

Jurnal Sisfokom, 2020
Cancer is one of the deadliest diseases in the world that needs to be handled as early as possible. One of the methods to detect the presence of cancer cells early on is by using microarray data. Microarray data can store human gene expression and use it
Muhammad Naufal Mukhbit Amrullah, Adiwijaya Adiwijaya, Widi Astuti   +2 more
doaj   +1 more source

Novel Adaptive Bayesian Regularization Networks for Peristaltic Motion of a Third-Grade Fluid in a Planar Channel

Mathematics, 2022
In this presented communication, a novel design of intelligent Bayesian regularization backpropagation networks (IBRBNs) based on stochastic numerical computing is presented.
Tariq Mahmood, Nasir Ali, Naveed Ishtiaq Chaudhary, Khalid Mehmood Cheema, Ahmad H. Milyani, Muhammad Asif Zahoor Raja   +5 more
doaj   +1 more source

Learning in Feedforward Neural Networks Accelerated by Transfer Entropy

Entropy, 2020
Current neural networks architectures are many times harder to train because of the increasing size and complexity of the used datasets. Our objective is to design more efficient training algorithms utilizing causal relationships inferred from neural ...
Adrian Moldovan, Angel Caţaron, Răzvan Andonie   +2 more
doaj   +1 more source

An Agent-Based Model to Reproduce the Boolean Logic Behaviour of Neuronal Self-Organised Communities through Pulse Delay Modulation and Generation of Logic Gates

Biomimetics
The human brain is arguably the most complex “machine” to ever exist. Its detailed functioning is yet to be fully understood, let alone modelled. Neurological processes have logical signal-processing and biophysical aspects, and both affect the brain’s ...
Luis Irastorza-Valera, José María Benítez, Francisco J. Montáns, Luis Saucedo-Mora   +3 more
doaj   +1 more source

Redes neurais e suas aplicações em calibração multivariada Neural networks and its applications in multivariate calibration

Química Nova, 2001
Neural Networks are a set of mathematical methods and computer programs designed to simulate the information process and the knowledge acquisition of the human brain. In last years its application in chemistry is increasing significantly, due the special
Eduardo O. de Cerqueira, João C. de Andrade, Ronei J. Poppi, Cesar Mello   +3 more
doaj   +1 more source

Target Classification in Synthetic Aperture Radar Images Using Quantized Wavelet Scattering Networks

Sensors, 2021
The need to classify targets and features in high-resolution imagery is of interest in applications such as detection of landmines in ground penetrating radar and tumors in medical ultrasound images.
Raghu G. Raj, Maxine R. Fox, Ram M. Narayanan   +2 more
doaj   +1 more source