9190744
A gradient BYY harmony learning rule on Gaussian mixture with automated model selection
Abstract One important feature of Bayesian Ying–Yang (BYY) harmony learning is that model selection can be made automatically during parametric learning. In this paper, BYY harmony learning with a bi-directional architecture is studied for Gaussian mixture modelling via a gradient learning rule. It has been demonstrated by simulation experiments that the number of Gaussians can be determined automatically during learning the parameters of the Gaussian mixture.
6431369
A Neural Network Approach to Real-Time Pattern Recognition
This paper presents a new neural network approach to real-time pattern recognition on a given set of binary (or bipolar) sample patterns. The perceptive neuron of a binary pattern is defined and constructed as a binary neuron with a neighborhood perceptive field. Letting its hidden units be the respective perceptive neurons of the patterns, a three-layer forward neural network is constructed to recognize these patterns with minimum error probability in a noisy environment. The theoretical and simulation analyses show that the network is effective for pattern recognition and can be under strict real-time constraints.
370694
Further Results on the Asymptotic Memory Capacity of the Generalized Hopfield Network
This paper presents a further theoretical analysis on the asymptotic memory capacity of the generalized Hopfield network (GHN) under the perceptron learning scheme. It has been proved that the asymptotic memory capacity of the GHN is exactly 2(n− 1), where n is the number of neurons in the network. That is, the GHN of n neurons can store 2(n− 1) bipolar sample patterns as its stable states when n is large, which has significantly improved the existing results on the asymptotic memory capacity of the GHN.
361698
The Mahalanobis Distance Based Rival Penalized Competitive Learning Algorithm
The rival penalized competitive learning (RPCL) algorithm has been developed to make the clustering analysis on a set of sample data in which the number of clusters is unknown, and recent theoretical analysis shows that it can be constructed by minimizing a special kind of cost function on the sample data. In this paper, we use the Mahalanobis distance instead of the Euclidean distance in the cost function computation and propose the Mahalanobis distance based rival penalized competitive learning (MDRPCL) algorithm. It is demonstrated by the experiments that the MDRPCL algorithm can be successful to determine the number of elliptical clusters in a data set and lead to a good classification result.
6071992
The asymptotic memory capacity of the generalized Hopfield network
This paper presents a theoretical analysis on the asymptotic memory capacity of the generalized Hopfield network. The perceptron learning scheme is proposed to store sample patterns as the stable states in a generalized Hopfield network. We have obtained that (n-1) and 2n are a lower and an upper bound of the asymptotic memory capacity of the network of n neurons, respectively, which shows that the generalized Hopfield network can store the larger number of sample patterns than Hopfield network.
1465121
MFCC and SVM Based Recognition of Chinese Vowels
The recognition of vowels in Chinese speech is very important for Chinese speech recognition and understanding. However, it is rather difficult and there has been no efficient method to solve it yet. In this paper, we propose a new approach to the recognition of Chinese vowels via the support vector machine (SVM) with the Mel-Frequency Cepstral Coefficients (MFCCs) as the vowel’s features. It is shown by the experiments that this method can reach a high recognition accuracy on the given vowels database and outperform the SVM with the Linear Prediction Coding Cepstral (LPCC) coefficients as the vowel’s features.
3476455
Simulation Study of AODV Performance over IEEE 802.15.4 MAC in WSN with Mobile Sinks
Mobility has been incorporated into wireless sensor networks in recent years in order to improve energy efficiency and network coverage. In particular, at the cost of increased message delivery delay, the energy conservation can be achieved by limiting the hop count between the communicating sensor-sink pair. In this paper we allow multihop routing between one sensor and mobile sinks, and consider the delay*energy metric, which is a compound metric to evaluate the performance of diverse data collection schemes. Through extensive simulation experiments of AODV performance over IEEE 802.15.4 MAC with clustered wireless sensor network setting, we investigate the fundamental problems of AODV without information of 802.15.4 MAC, and analyze the influence of incorporating multiple sinks.
15963814
A Multiplatform P2P System: its implementation and applications
Peer-to-peer (P2P) computing offers many attractive features, such as collaboration, self-organization, load balancing, availability, fault tolerance and anonymity. However, it also faces many serious challenges. In our previous work, we implemented a synchronous P2P collaboration platform called TOMSCOP. Based on the elementary peer group services offered by the JXTA general framework, TOMSCOP provides the extra four types of services: synchronous message transportation, peer room administration, peer communication support and application space management. By using the four services, different kinds of shared applications for various specific purposes can be relatively easily developed and associated collaborative cyber spaces or communities can be quickly built across the JXTA virtual network overlaid on top of the existing physical networks. However, the TOMSCOP was implemented only in Windows XP OS. In this paper, we extend our previous work and present the implementation of a Multi-Platform P2P System (MPPS). The proposed system operates very smoothly in UNIX Solaris 9 OS, LINUX Suse 9.1 OS, Mac OSX, and Windows XP. In the future study, we would like to evaluate the implemented P2P platform and compare its performance with other P2P systems.
22258067
A principled approach for formative Web learning assessment and adaptive tutoring
Web based distance learning is a trend of instruction delivery. One of the most difficult challenges of such a learning mechanism is the assessment of students' learning criteria. It is hard to judge the behavior of a student since the instructor is separated spatially and temporally from the students. However, it is possible to rely on some Web based tools to keep track of a student's course attendance, as well as the navigation behavior of that student. In addition, the navigation behavior of an individual can be compared to those of others. Analysis can be conducted, and an interactive tutorial can be generated to assist the student with a poor score. The paper proposes such a mechanism, as well as its supporting system run on Windows browsers.
2850355
An Optimal Node Selection Scheme in Multi-hop Wireless Network
In this paper, a cooperative wireless multi-hop network is considered, cooperative diversity can be realized by allowing nodes close proximity to cooperate in transmission. In order to group receiver nodes into a cluster, it is necessary to select appropriate nodes. We introduce an optimal node selection algorithm based on MIMO antenna selection, this algorithm, combining with cooperative transmission strategy, gives an optimal node selection algorithm using convex optimization theory. Theoretical analysis and simulation indicate that this scheme can give good performance of maximizing the channel capacity through optimal node selection.
16576508
Ubisafe Computing: Vision and Challenges (I)
In recent years, a variety of new computing paradigms have been proposed for various purposes. It is true that many of them intend to and really can gratify some of the people sometime, somewhere; a few of them can even gratify some of the people anytime, anywhere. However, at present, none of the computing paradigms intend to gratify all the people anytime, anywhere. With the rapid advance of information technology and the spread of information services, the IT disparity in age, social standing, and race of the people has been expanding and has become a critical social problem of the 21st century. Thus, we have a fundamental question: Can we construct, in a unified methodology, a computing environment that can gratify all the people in all situations, all places and all the time? We propose a novel and inclusive computing paradigm, named ubisafe computing, for studying and providing possible solutions to the above problem. The ultimate goal of ubisafe computing is to build a computing environment in which all people and organizations can benefit from ubiquitous services anytime anywhere with assured and desired satisfaction without worrying or thinking about safety. That is, the ubisafe computing vision emphasizes two basic aspects: ubiquitous safety and ubiquitous satisfaction to all people in all situations. This paper presents the motivations for the ubisafe computing vision but focuses on one basic aspect of ubiquitous safety that covers reliability, security, privacy, persistency, trust, risk, out of control, and other watchfulness while considering novel, essential ubicomp or percomp features of unobtrusive computers, diverse users/people and life-like systems.