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Artificial neural networks (ANNs) have been successfully applied to solve a variety of classification and function approximation problems. Although ANNs can generally predict better than decision trees for pattern classification problems,…

Neural and Evolutionary Computing · Computer Science 2010-09-28 S. M. Kamruzzaman , Md. Monirul Islam

A Mobile Ad hoc network (MANET) consists of nodes which use multi-hop communication to establish connection between nodes. Traditional infrastructure based systems use a centralized architecture for address allocation. However, this is not…

Networking and Internet Architecture · Computer Science 2016-05-03 Akshay Khatri , Sankalp Kolhe , Nupur Giri

In recent years, deep learning has been a revolution in the field of machine learning, for computer vision in particular. In this approach, a deep (multilayer) artificial neural network (ANN) is trained in a supervised manner using…

Neural and Evolutionary Computing · Computer Science 2019-01-23 Amirhossein Tavanaei , Masoud Ghodrati , Saeed Reza Kheradpisheh , Timothee Masquelier , Anthony S. Maida

In recent years, artificial neural networks (ANNs) have won numerous contests in pattern recognition and machine learning. ANNS have been applied to problems ranging from speech recognition to prediction of protein secondary structure,…

Data Analysis, Statistics and Probability · Physics 2021-07-09 Kanhaiya Gupta

Mobility performance has been a key focus in cellular networks up to 5G. To enhance handover (HO) performance, 3GPP introduced Conditional Handover (CHO) and Layer 1/Layer 2 Triggered Mobility (LTM) mechanisms in 5G. While these reactive HO…

Networking and Internet Architecture · Computer Science 2025-09-30 Ana Gonzalez Bermudez , Miquel Farreras , Milan Groshev , José Antonio Trujillo , Isabel de la Bandera , Raquel Barco

The de facto algorithm for training the back pass of a feedforward neural network is backpropagation (BP). The use of almost-everywhere differentiable activation functions made it efficient and effective to propagate the gradient backwards…

Neural and Evolutionary Computing · Computer Science 2022-06-14 John Waldo

Backpropagation algorithm is the cornerstone for neural network analysis. Paper extends it for training any derivatives of neural network's output with respect to its input. By the dint of it feedforward networks can be used to solve or…

Neural and Evolutionary Computing · Computer Science 2017-12-13 V. I. Avrutskiy

With the explosive growth in demand for mobile traffic, one of the promising solutions is to offload cellular traffic to small base stations for better system efficiency. Due to increasing system complexity, network operators are facing…

Networking and Internet Architecture · Computer Science 2020-05-19 Chih-Wei Huang , Po-Chen Chen

In wireless sensor networks (WSNs), the opportunistic routing has better performances on packet delivery probability than the deterministic routing. For reducing the transmission delay and duplicate transmission in opportunistic routing,…

Networking and Internet Architecture · Computer Science 2019-12-18 Ning Li , Alex X. Liu , Jose-Fernan Martinez-Ortega , Vicente Hernandez Diaz , Xin Yuan

The choice of architecture of artificial neuron network (ANN) is still a challenging task that users face every time. It greatly affects the accuracy of the built network. In fact there is no optimal method that is applicable to various…

Neural and Evolutionary Computing · Computer Science 2014-12-18 Cyrine Arouri , Engelbert Mephu Nguifo , Sabeur Aridhi , Cécile Roucelle , Gaelle Bonnet-Loosli , Norbert Tsopzé

Randomized backoff protocols, such as exponential backoff, are a powerful tool for managing access to a shared resource, often a wireless communication channel (e.g., [1]). For a wireless device to transmit successfully, it uses a backoff…

Data Structures and Algorithms · Computer Science 2022-07-26 Michael A. Bender , Seth Gilbert , Fabian Kuhn , John Kuszmaul , Muriel Médard

The handover (HO) procedure is one of the most critical functions in a cellular network driven by measurements of the user channel of the serving and neighboring cells. The success rate of the entire HO procedure is significantly affected…

Machine Learning · Computer Science 2024-11-18 Dino Pjanić , Alexandros Sopasakis , Andres Reial , Fredrik Tufvesson

Handwriting is one of the most important means of daily communication. Although the problem of handwriting recognition has been considered for more than 60 years there are still many open issues, especially in the task of unconstrained…

Artificial Intelligence · Computer Science 2013-01-22 Firoj Parwej

Error backpropagation is an extremely effective algorithm for assigning credit in artificial neural networks. However, weight updates under Backprop depend on lengthy recursive computations and require separate output and error messages --…

Machine Learning · Computer Science 2014-11-25 David Balduzzi , Hastagiri Vanchinathan , Joachim Buhmann

Artificial neural networks have been successfully applied to a variety of business application problems involving classification and regression. Although backpropagation neural networks generally predict better than decision trees do for…

Neural and Evolutionary Computing · Computer Science 2010-09-28 S. M. Kamruzzaman , Ahmed Ryadh Hasan

We introduce a new programming language and its categorical semantics in order to design and implement neural networks within the framework of algebraic effects and handlers for arrows. Our language enables us to construct neural networks…

Programming Languages · Computer Science 2026-02-23 Takahiro Sanada , Keisuke Hoshino , Kenshin Hirai , Shin-ya Katsumata

The growing deployment of drones in a myriad of applications relies on seamless and reliable wireless connectivity for safe control and operation of drones. Cellular technology is a key enabler for providing essential wireless services to…

Information Theory · Computer Science 2020-05-12 Yun Chen , Xingqin Lin , Talha Ahmed Khan , Mohammad Mozaffari

Handover measurement is responsible for finding a handover target and directly decides the performance of mobility management. It is governed by a complex combination of parameters dealing with multi-cell scenarios and system dynamics. A…

Networking and Internet Architecture · Computer Science 2015-02-03 Van Minh Nguyen , Chung Shue Chen , Laurent Thomas

Artificial neural network (ANN) has been widely used due to its strong nonlinear mapping ability, fault tolerance and self-learning ability. This article summarizes the development history of artificial neural networks, introduces three…

Systems and Control · Electrical Eng. & Systems 2021-10-12 Fei Liang , Taowen Zhang

Offering of different attractive opportunities by different wireless technologies trends the convergence of heterogeneous networks for the future wireless communication system. To make a seamless handover among the heterogeneous networks,…

Multimedia · Computer Science 2011-03-07 Mostafa Zaman Chowdhury , Yeong Min Jang