Preferred Language
Articles
/
jih-968
On Comparison between Radial Basis Function and Wavelet Basis Functions Neural Networks
...Show More Authors

      In this paper we study and design two feed forward neural networks. The first approach uses radial basis function network and second approach uses wavelet basis function network to approximate the mapping from the input to the output space. The trained networks are then used in an conjugate gradient algorithm to estimate the output. These neural networks are then applied to solve differential equation. Results of applying these algorithms to several examples are presented

View Publication Preview PDF
Quick Preview PDF
Publication Date
Fri Jun 01 2007
Journal Name
Journal Of Al-nahrain University Science
ON THE GREEDY RADIAL BASIS FUNCTION NEURAL NETWORKS FOR APPROXIMATION MULTIDIMENSIONAL FUNCTIONS
...Show More Authors

The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Wed Sep 12 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Comparison between Multi-Layer Perceptron and Radial Basis Function Networks in Detecting Humans Based on Object Shape
...Show More Authors

       Human detection represents a main problem of interest when using video based monitoring. In this paper, artificial neural networks, namely multilayer perceptron (MLP) and radial basis function (RBF) are used to detect humans among different objects in a sequence of frames (images) using classification approach. The classification used is based on the shape of the object instead of depending on the contents of the frame. Initially, background subtraction is depended to extract objects of interest from the frame, then statistical and geometric information are obtained from vertical and horizontal projections of the objects that are detected to stand for the shape of the object. Next to this step, two ty

... Show More
View Publication Preview PDF
Crossref
Publication Date
Fri Dec 23 2011
Journal Name
International Journal Of The Physical Sciences
Fast prediction of power transfer stability index based on radial basis function neural network
...Show More Authors

View Publication
Scopus (16)
Crossref (4)
Scopus Crossref
Publication Date
Mon Jun 30 2008
Journal Name
Iraqi Journal Of Science
On the Greedy Ridge Function Neural Networks for Approximation Multidimensional Functions
...Show More Authors

The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).

Preview PDF
Publication Date
Sun Apr 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Influence Activation Function in Approximate Periodic Functions Using Neural Networks
...Show More Authors

The aim of this paper is to design fast neural networks to approximate periodic functions, that is, design a fully connected networks contains links between all nodes in adjacent layers which can speed up the approximation times, reduce approximation failures, and increase possibility of obtaining the globally optimal approximation. We training suggested network by Levenberg-Marquardt training algorithm then speeding suggested networks by choosing most activation function (transfer function) which having a very fast convergence rate for reasonable size networks.             In all algorithms, the gradient of the performance function (energy function) is used to determine how to

... Show More
View Publication Preview PDF
Publication Date
Thu Jun 15 2023
Journal Name
Journal Of Legal Sciences
Smart Contract: Theoretical Basis and Application Dialectic
...Show More Authors

This study focuses on the relationship of the smart contracts and legal application in the field of civil and commercial contracts. The study aimed to anticipate the possibility of issuing a new law in the future, Nowadays, smart contracts t is a legal challenge that cannot be ignored, Despite the UAE legislator’s interest in artificial intelligence technologies and studying them from the legislative aspect, especially in the field of self-driving cars and the use of robots, and looking forward to a global leadership in the field of Block chain, it is still early to talk about bringing the Block chain to the ground of legislative reality in light of the challenges and risks arising from many challenges that We discussed them in this co

... Show More
View Publication Preview PDF
Crossref
Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Comparison Study of Electromyography Using Wavelet and Neural Network
...Show More Authors

In this paper we present a method to analyze five types with fifteen wavelet families for eighteen different EMG signals. A comparison study is also given to show performance of various families after modifying the results with back propagation Neural Network. This is actually will help the researchers with the first step of EMG analysis. Huge sets of results (more than 100 sets) are proposed and then classified to be discussed and reach the final.

View Publication Preview PDF
Publication Date
Sat Dec 31 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Estimation of nonparametric regression function using shrinkage wavelet and different mother functions
...Show More Authors

View Publication
Scopus Crossref
Publication Date
Thu Aug 03 2023
Journal Name
Journal Of Legal Sciences
The Legal Basis for Negotiations in International Armed Conflicts
...Show More Authors

Negotiations are among the best means that countries use to achieve their various objectives in foreign policy, precisely because of the high degree of influence that this tool exerts in this field, and the extent of its link with other peaceful diplomatic means.

On the other hand, negotiations represent the best way to move away from the option of war or perhaps settle it. This is mainly related to the efforts of states to employ this method as a method for dealings among themselves, and thus negotiations represent a supreme value that is indispensable for states, as they represent a clear and universally accepted method of work related to the maintenance of peace and security International as a culture in the relations of state

... Show More
View Publication Preview PDF
Publication Date
Fri Sep 06 2024
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Wavelet Transformations to Estimate Nonparametric Regression Function
...Show More Authors

The purpose of this article is to improve and minimize noise from the signal by studying wavelet transforms and showing how to use the most effective ones for processing and analysis. As both the Discrete Wavelet Transformation method was used, we will outline some transformation techniques along with the methodology for applying them to remove noise from the signal. Proceeds based on the threshold value and the threshold functions Lifting Transformation, Wavelet Transformation, and Packet Discrete Wavelet Transformation. Using AMSE, A comparison was made between them , and the best was selected. When the aforementioned techniques were applied to actual data that was represented by each of the prices, it became evident that the lift

... Show More
Crossref