• Title/Summary/Keyword: FMMNN

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A Study on Performance Improvement of Fuzzy Min-Max Neural Network Using Gating Network

  • Kwak, Byoung-Dong;Park, Kwang-Hyun;Z. Zenn Bien
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.492-495
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    • 2003
  • Fuzzy Min-Max Neural Network(FMMNN) is a powerful classifier, It has, however, some problems. Learning result depends on the presentation order of input data and the training parameter that limits the size of hyperbox. The latter problem affects the result seriously. In this paper, the new approach to alleviate that without loss of on-line learning ability is proposed. The committee machine is used to achieve the multi-resolution FMMNN. Each expert is a FMMNN with fixed training parameter. The advantages of small and large training parameters are used at the same time. The parameters are selected by performance and independence measures. The Decision of each expert is guided by the gating network. Therefore the regional and parametric divide and conquer scheme are used. Simulation shows that the proposed method has better classification performance.

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Development of Attack Intention Extractor for Soccer Robot system (축구 로봇의 공격 의도 추출기 설계)

  • 박해리;정진우;변증남
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.40 no.4
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    • pp.193-205
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    • 2003
  • There has been so many research activities about robot soccer system in the many research fields, for example, intelligent control, communication, computer technology, sensor technology, image processing, mechatronics. Especially researchers research strategy for attacking in the field of strategy, and develop intelligent strategy. Then, soccer robots cannot defense completely and efficiently by using simple defense strategy. Therefore, intention extraction of attacker is needed for efficient defense. In this thesis, intention extractor of soccer robots is designed and developed based on FMMNN(Fuzzy Min-Max Neural networks ). First, intention for soccer robot system is defined, and intention extraction for soccer robot system is explained.. Next, FMMNN based intention extractor for soccer robot system is determined. FMMNN is one of the pattern classification method and have several advantages: on-line adaptation, short training time, soft decision. Therefore, FMMNN is suitable for soccer robot system having dynamic environment. Observer extracts attack intention of opponents by using this intention exactor, and this intention extractor is also used for analyzing strategy of opponent team. The capability of developed intention extractor is verified by simulation of 3 vs. 3 robot succor simulator. It was confirmed that the rates of intention extraction each experiment increase.

Soft-Remote-Control System based on EMG Signals for the Intelligent Sweet Home

  • Song, Jae-Hoon;Han, Jeong-Su;Pak, Ji-Woo;Kim, Dae-Jin;Jung, Jin-Woo;Bien, Z. Zenn;Lee, He-Young
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1163-1168
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    • 2005
  • This paper proposes a soft-remote-control (soft-remocon) system based on EMG signals for the Intelligent Sweet Home. The proposed system is applied to Intelligent Sweet Home which was developed to help the independence living of the elderly and physically handicapped individuals. The goal of proposed system is to control home-installed electronic devices such as TV, air-conditioner, curtain and lamp in Intelligent Sweet Home using EMG signals. Features such as VAR and DAMV having good separability performance are selected for pattern classification. FMMNN is adopted as a pattern classifier. Classification results are allowed to a developed remote control module and then corresponding infrared pulses can operate home-installed electronic devices. We concluded that EMG as an input interface for home-installed electronic devices in Intelligent Sweet Home.

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A Fuzzy Min-Max Neural Network(FMMNN) Based Gait Phase Classification Method using Electromyography(EMG) Signal (근전도 신호를 이용한 퍼지 최대-최소 신경망 기반 보행 단계 분류 방법)

  • Yi, Tae-Youb;Lee, Sang-Wan;Jang, Hyo-Young;Kim, Heon-Hui;Jung, Jin-Woo;Bien, Zeung-Nam
    • 한국HCI학회:학술대회논문집
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    • 2007.02a
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    • pp.841-847
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    • 2007
  • 최근 삶의 수준의 향상과 의학 기술의 발전으로 노인 인구가 증가하고 있다. 하지만 늘어나는 노인 인구에 비례하여 신체적 노화로 거동이 어려운 노인의 수 또한 증가하는 추세이다. 실제로 많은 노인 인구가 거동이 불편해 정상적인 생활을 하지 못하고 있기 때문에 보행 시 적절한 힘을 보조해 줄 수 있는 보행 보조 장치의 개발이 필요하다. 이 같은 보행 보조 장치를 개발함에 있어 보행자의 보행 패턴이 고려된다면 보행자의 걸음걸이에 맞춰 자연스럽게 힘을 보조해 줄 수 있기 때문에 보행자의 보행 단계 분류에 관한 연구가 선행되어야 한다. 그래서 본 논문에서는 하지 근전도 신호를 이용해 보행 단계를 구분하는 방법을 제안하고자 한다. 근전도 신호는 근육이 움직일 때 발생하는 아주 작은 전기적인 신호이다. 근전도 신호는 작은 잡음에도 민감하며, 전극을 부착하는 근육의 위치에 따라서도 값의 차이가 크기 때문에 근전도 신호의 획득 및 처리 방법이 중요하다. 위를 위해 피실험자 별 근육의 위치와 보행 속도를 달리하여 근전도 신호를 획득하고 획득한 신호로부터 여러 특징 값을 추출한다. 그리고 새로운 데이터에 대해 적응성이 강하고 시간에 따라 변하는 근전도 신호의 특성을 잘 반영할 수 있으며 각 집합(class)의 비선형 분리가 가능한 퍼지 최대-최소 신경망(Fuzzy Min-Max Neural Network: FMMNN)을 이용해 보행 단계를 분류해 본다. 실험 결과를 통해 제안한 방법의 타당성을 검증해 보고 보행자, 보행속도, 근전도 측정을 위한 근육의 위치가 보행 패턴 분류에 미치는 영향을 알아본다.

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Study on Intelligent Autonomous Navigation of Avatar using Hand Gesture Recognition (손 제스처 인식을 통한 인체 아바타의 지능적 자율 이동에 관한 연구)

  • 김종성;박광현;김정배;도준형;송경준;민병의;변증남
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.483-486
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    • 1999
  • In this paper, we present a real-time hand gesture recognition system that controls motion of a human avatar based on the pre-defined dynamic hand gesture commands in a virtual environment. Each motion of a human avatar consists of some elementary motions which are produced by solving inverse kinematics to target posture and interpolating joint angles for human-like motions. To overcome processing time of the recognition system for teaming, we use a Fuzzy Min-Max Neural Network (FMMNN) for classification of hand postures

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EMG Pattern Classification using Soft Computing Techniques and Its Application to the Control of a Rehabilitation Robotic Arm (소프트 컴퓨팅 기법을 이용한 근전도 신호의 패턴 분류와 재활 로봇 팔 제어에의 응용)

  • Han, Jeong-Su;Kim, Jong-Seong;Song, Won-Gyeong;Bang, Won-Cheol;Lee, Hui-Yeong;Byeon, Jeung-Nam
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.37 no.6
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    • pp.50-63
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    • 2000
  • In this paper, a new EMG pattern classification method based on soft computing techniques is proposed to help the disabled and the elderly handle rehabilitation robotic arm systems. First, it is shown that EMG is more useful than existing input devices such as voice, a laser pointer and a keypad in view of naturality, extensibility, and applicability. Then, a new procedure is proposed to select the minimal feature set. As methods of classifying the pre-defined motions, a fuzzy pattern classification and fuzzy min-max neural networks (FMMNN) are designed using the selected features. As results, the motions are recognized with success rates of 83 percent and 90 Percent using fuzzy pattern classification and FMMNN, respectively.

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A Study on Feature selection based the Fuzzy Min-Max Neural Network and Application on Gait Phase recognition using EMG (퍼지 최대-최소 신경망을 이용한 특징 집합 선택에 관한 연구 및 보행 단계인식에의 응용)

  • Lee, Tae-Yeop;Lee, Sang-Wan;Byeon, Jeung-Nam
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.11a
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    • pp.167-171
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    • 2007
  • 본 논문은 패턴 분류 문제에 사용되는 퍼지 최대-최소 신경망 방법을 이용하여 특정 집합으로부터 새로운 특정 집합을 추출해내고 추출된 특정 집합으로부터 의미 있는 특정을 선택해 내는 새로운 방법을 제안한다. 퍼지 최대-최소 신경망은 패턴 분류를 위해 주로 사용이 되어 왔지만, 퍼지 최대-최소 신경망을 이용해 특정 집합의 값들을 패턴 공간내의 초상자의 집합으로 변환하고 변환된 초상자들끼리의 인접성을 척도로 단순한 연산을 통한 빠른 특정 집합을 선택하게 된다. 마지막으로 본 논문의 특정 집합 선택 방법을 하지 근전도 신호를 이용한 보행 패턴 분류에 적용해 보고, 그 결과를 기존 여러 특정 집합 선태 방법들과 비교해 봄으로써 제안한 방법의 타당성 및 적용 가능성을 알아본다.

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Development of an EMG-based Powered Wheelchair Controller for Users with High-level Spinal Cord Injury

  • Han, Jeong-Su;Dimitar H. Stefanov;Lee, Hae-Beom;Kim, Dae-Jin;Song, Won-Kyung;Z. Zenn Bien;Park, Kwang-Hyun;Kim, Jong-sung
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.84.5-84
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    • 2001
  • The objective of this paper is to develop a powered wheelchair controller based on EMG for users with high-level spinal cord injury. EMG is very naturally measured when the user Indicating a certain direction, and the force information which will be used for the speed of wheelchair is easily extracted from EMG. Furthermore, the emergency situation based on EMG will be checked relatively ease. We classified the pre-defined motions such as rest case, forward movement, left movement, and right movement by Fuzzy Min-Max Neural Networks (FMMNN). This classification results shows the feasibility of EMG as an input interface for powered wheelchair. To make the system low cost and small size, we developed EMG AMP and its controller ...

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