• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2000.11a
• /
• pp.259-262
• /
• 2000

In this paper, an Adaptive neuro-fuzzy Inference system(ANFIS) using fuzzy min-max network(FMMN) is proposed. Fuzzy min-max network classifier that utilizes fuzzy sets as pattern classes is described. Each fuzzy set is an aggregation of fuzzy set hyperboxes. Here, the proposed method transforms the hyperboxes into gaussian menbership functions, where the transformed membership functions are inserted for generating fuzzy rules of ANFIS. Finally, we applied the proposed method to the classification problem of iris data and obtained a better performance than previous works.

• Honam Mathematical Journal
• /
• v.35 no.4
• /
• pp.729-738
• /
• 2013

In this paper, we investigate a localized approximation of a continuously differentiable function by neural networks. To do this, we first approximate a continuously differentiable function by B-spline functions and then approximate B-spline functions by neural networks. Our proofs are constructive and we give numerical results to support our theory.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.367-367
• /
• 2000

In this paper, an Adaptive neuro-fuzzy Inference system(ANFIS) using fuzzy min-max network(FMMN) is proposed. Fuzzy min-max network classifier that utilizes fuzzy sets as pattern classes is described. Each fuzzy set is an aggregation of fuzzy set hyperboxes. Here, the proposed method transforms the hyperboxes into gaussian membership functions, where the transformed membership functions are inserted for generating fuzzy rules of ANFIS. Finally, we applied the proposed method to the classification problem of iris data and obtained a better performance than previous works.

• Annual Conference of KIPS
• /
• 2013.05a
• /
• pp.972-975
• /
• 2013

This work developed a code analysis & extraction tool named Function Network Analyzer (FNA) to reduce the cost of software safety analysis. FNA analyzes functions and variables which a given function depends on, and extracts subset of code that can be compiled of automotive operating system, final resulting a well-ordered code sequence that can be compiled for model checking technique. And the experimental result illustrates that FNA can get 100% accurate rate and over 96% reduction rate by testing API functions from trampoline system.

• Journal of the Korea Society for Simulation
• /
• v.8 no.4
• /
• pp.125-136
• /
• 1999

In the forthcoming public ATM/B-ISDN, the efficient resource management with pre-planned transit networking which public domain NNI signaling is essential to maintain high network utilization and to assure QoS to the multimedia service users. For this purpose the transit networks must be managed according to the bearer service capability which is defined by ATM Forum and ITU-T. In this paper, we introduce an implementation of ATM transit networking with ATM VP-XC(Virtual Path cross-connect) and US(Network Management System). The functions of ATM VP-XC and NMS have been simulated with OPNET 6.1 modules. We implemented the F4 OAM functions of ATM VP connection according to the ITU-T 1.610 recommendation. Also, the ATM VP transit networking is managed by the NMS according to the connection management architecture of the TWN(Telecommunications Management Network) /TINA ( Telecommunications Information Networking Architecture).

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.12A
• /
• pp.1985-1991
• /
• 1999

In this paper, complete and general two-port lumped Spice-network model is developed for a lossy transmission line. This model is realized as a Spice subcircuit, by means of standard lumped network elements and mathematical functions. It is used as a component in the time-domain simulation of a high-speed data transmission line such as IMI(Inter Module Interface) data path in HANbit ACE 64 ATM switching system. The only required Spice network elements are resistance and frequency-dependent controlled-voltage sources. Such frequency-dependent sources are realized by utilizing the standard Hspice mathematical functions FREQ, DELAY, and POLY.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1996.10a
• /
• pp.243-248
• /
• 1996

In this paper, a general neural-network-based connectionist model, called Fuzzy Neural Network(FNN), is proposed for the realization of a fuzzy logic control system. The proposed FNN is a feedforward multi-layered network which integrates the basic elements and functions of a traditional fuzzy logic controller into a connectionist structure which has distributed learning abilities. Such FNN can be constructed from training examples by learning rule, and the connectionist structure can be trained to develop fuzzy logic rules and find optimal input/output membership functions. Computer simulation examples will be presented to illustrate the performance and applicability of the proposed FNN, and their associated learning algorithms.

• Journal of Communications and Networks
• /
• v.12 no.3
• /
• pp.253-265
• /
• 2010

The problem of pricing for a telecommunication network is investigated with respect to the users' sensitivity to the pricing structure. A functional optimization problem is formulated, in order to compute price reallocations as functions of data collected in real time during the network evolution. No a-priori knowledge about the users' utility functions and the traffic demands is required, since adaptive reactions to the network conditions are sought in real time. To this aim, a neural approximation technique is studied to exploit an optimal pricing control law, able to counteract traffic changes with a small on-line computational effort. Owing to the generality of the mathematical framework under investigation, our control methodology can be generalized for other decision variables and cost functionals.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.41 no.8
• /
• pp.914-921
• /
• 1992

In this paper, we introduce a Walsh network and an LMS algorithm, and show how these can be realized as an adaptive equalizer. The Walsh network is built from a set of Walsh and Block pulse functions. In the LMS algorithm, the convergence factor is an important design parameter because it governs stability and convergence speed, which depend on the proper choice of the convergence facotr. The conventional adaptation techniques use a fixed time constant convergence factor by the method of trial and error. In this paper, we propose an optimal method in the choice of the convergence factor. The proposed algorithm depends on the received signal and the output of the Walsh network in real time.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.22 no.3
• /
• pp.580-592
• /
• 1997

Since an ATM network consists of a number of VPC/VCC requiring various QoS requirements, the end-to-end QoS for each VPC/VCC should be guaranteed. Although many research works on the traffic control are under study to guarantee the QoS, there have been research efforts to reflect the results of network management functions into the traffic control mechanism. To effectively make use of the performance management functions into the VPC/VCC management, threre is a need for the network manager to rapidly retrieve the relevant information. In this research, the mechanism to effectively retrieve the management information using SNMP is suggested. First of all, we construct the MIBs in the agent for the corresponding VPC/VCC. Also, we suggest the way to retrieve MIB with minimum cost. Mathematical analysis shows that the proposed technique has better performance than that using the existing SNMP.