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Full-Text Articles in Engineering
Configuring The Radial Basis Function Neural Network, Insoo Sohn
Configuring The Radial Basis Function Neural Network, Insoo Sohn
Theses
The most important factor in configuring an optimum radial basis function (RBF) network is the training of neural units in the hidden layer. Many algorithms have been proposed, e.g., competitive learning (CL), to train the hidden units. CL suffers from producing "dead-units." The other major factor Which was ignored in the past is the appropriate selection of the number of neural units in the hidden layer. The frequency sensitive competitive learning (FSCL) algorithm was proposed to alleviate the problem of dead-units, but it does not alleviate the latter problem. The rival penalized competitive learning (RPCL) algorithm is an improved version …
A New Method To Optimize The Satellite Broadcasting Schedules Using The Mean Field Annealing Of A Neural Network, Youyi Yu
Theses
This thesis reports a new method for optimizing satellite broadcasting schedules based on the Hopfield neural model in combination with the mean field annealing theory. A clamping technique is used with an associative matrix, thus reducing the dimensions of the solution space. A formula for estimating the critical temperature for the mean field annealing procedure is derived, hence enabling the updating of the mean field theory equations to be more economical. Several factors on the numerical implementation of the mean field equations using a straightforward iteration method that may cause divergence are discussed; methods to avoid this kind of divergence …
The Neural Network Based Control System For Dynamic Channel Allocation In Pcn Communications, Ching-Yao Huang
The Neural Network Based Control System For Dynamic Channel Allocation In Pcn Communications, Ching-Yao Huang
Theses
A neural network based control system (NNCS) is adopted in this paper to conduct the channel allocation task in the personal communication networks (PCN). Binary adaptive resonance theory (ART-1) that was modified for pattern matching and provided the corresponding responses is selected as the basic algorithm for the system. Digital portable radio technology can provide reliable access to high quality wireless service for many users. Low power transmission requirement and small cell size configuration that can support more users and diverse services than cellular radio system are the attractive attributes of PCN. Assigning multiple time slots to a user in …
The Bandwidth Allocation Of Atm Control By Neural Networks, Jin-Syan Chou
The Bandwidth Allocation Of Atm Control By Neural Networks, Jin-Syan Chou
Theses
In this thesis, we develop a neural network method based on Adaptive Resonance Theory to train and control the optimum bandwidth allocation of ATM network. In Broadband Integrated Service Digital Network (BISDN), the Asynchronous Transfer Mode (ATM) is already adopted as the transfer facility by CCITT. ATM is a high-bandwidth, low- delay, fast-packet switching and multiplexing technique. Using ATM technique, we can flexibly rearrange the network and reassign the bandwidth to meet the requirement of all types of services. As an effective optimization method, Genetic Algorithm (GA) is applied to implement the bandwidth allocation of ATM. Then, we use Adaptive …
Fast Packet Switching For B-Isdn With Neural Net Control, Ajit K. Chaudhuri
Fast Packet Switching For B-Isdn With Neural Net Control, Ajit K. Chaudhuri
Theses
The concept of integrated network where both the voice packet and data packet are delt with, started taking shape since 1970. Later, Users? demand for communication of data, voice, file, facsimile, image, videotext, videophone, videomovie has also been felt. All these services need bit rate of transmission in the order of 10, even 100 Mbits. An economical way to transmit this higher bit rate, with flexibility of bandwidth, is to treat voice/video in the form of packets and transmit those packets in real time. Studies of this kind of communication is carried out in Broadband ISDN ( BISDN). At this …
Comparative Study Of Prediction Gain Based On Neural Network Architecture, Prashant M. Shah
Comparative Study Of Prediction Gain Based On Neural Network Architecture, Prashant M. Shah
Theses
This thesis describes the Neural Network approach to design predictor using Delta and Generalized Delta Rule. The predictor is designed by supervised training based on the typical sequence of pixel values. Neural Network is used to find the coefficients of the predictor. Both 1-D and 2-D scheme of the pixels as well as linear and non-linear correlations are used to find the coefficients by training. Different combinations of pixels are used to find the "best" combination among the order of the predictor.
An Artificial Neural Network For Redundant Robot Inverse Kinematics Computation, Wibawa Utama
An Artificial Neural Network For Redundant Robot Inverse Kinematics Computation, Wibawa Utama
Theses
A redundant manipulator can be defined as a manipulator that has more degrees of freedom than necessary to determine the position and orientation of the end effector. Such a manipulator has dexterity, flexibility, and the ability to maneuver in presence of obstacles. One important and necessary step in utilizing a redundant robot is to relate the joint coordinates of the manipulator with the position and orientation of the end-effector. This specification is termed as the direct kinematics problem and can be written as x = f(q)
where x is a vector representing the position and orientation of the end-effector, q …