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AN APPROACH TO MODELING A BIONIC SELF ORGANIZATION AND FUNCTIONAL EXPRESSION
Hiroshi YOKOI,Yukinori KAKAZU 대한전자공학회 1992 대한전자공학회 학술대회 Vol.1992 No.10
This study is concerned how to construct a model of life as physical/mathematical representation. This model is called here a bionic model and vibrating potential field is introduced as fundamental world background of the model. Namely, required information creating/processing/controlling are done on this field. Especially this paper reports how to realize the simulation of a bionic self organization and its functional expression based on the mutual actions among a set of life units.
An Approach to Visual Pattern Recognition by Neural Network System
Yasuhiro HATAKEYAMA,Yukinori KAKAZU 대한전자공학회 1992 대한전자공학회 학술대회 Vol.1992 No.10
In this paper, a visual pattern recognition system is proposed, which can recognize both a pattern and its location. This system, referred to as the expanded neocognitron, has the following capabilities; (1) A higher performance in extraction of features, and (2) A new capability for recognizing the locations of patterns. This system adopts the learning and recognizing mechanism of the neocognitron. First, the ability to classify pattern is enhanced by improving the mechanisms of feature extraction and learning algorithm. Second, the function of detecting the location of each pattern is realized by developing an architecture which does not reduce structure, i.e., the unit density is constant all the way from the input stage to the output stage.
Modeling the Human Memory in Nerve Fields
Osamu FUJITA,Yukinori KAKAZU 대한전자공학회 1992 대한전자공학회 학술대회 Vol.1992 No.10
This paper describes the modeling of human memory using a nerve field model which is proposed for modeling the mechanism of brain mathmatically. In our model, two phases of memory, retention and recollection, are focused on. The former consists of two stages, short-term memory (STM) and long-term memory (LTM). The proposed model consists of three parts, the STM Layer, LTM Layer and the Intermediate Layer between them. Each of these is constructed by a nerve field. In the STM Layer, memorized information is retained dynamically in the form of the reverberating states of units within the layer, while in the LTM Layer, it is stored statically in the form of structures of the weight on the links between units. the Intermediate Layer is introduced to translate this dynamic representation in the STM Layer to the LTM Layer, and also to extract the static information from the STM Layer. In addition to this, we consider the recollection of information stored in the LTM. Finally, the behavior of this model is demonstrated by computer simulation.
A Study on New Control Mechanisms of Memory
Haibin LIU,Yukinori KAKAZU 대한전자공학회 1992 대한전자공학회 학술대회 Vol.1992 No.10
A physical phenomenon is observed through analysis of the Hodgkin-Huxley's model that is, according to Maxwell field equations a fired neuron can yield magnetic fields. The magnetic signals are an output of the neuron as some type of information, which may be supposed to be the conscious control information. Therefore, study on neural networks should take the field effect into consideration. Accordingly, a study on the behavior of a unit neuron in the field is made and a new neuron model is proposed. A mathematical Memory-Learning Relation has been derived from these new neuron equations, some concepts of memory and learning are introduced. Two learning theorems are put forward, and the control mechanisms of memory are also discussed. Finally, a theory, i.e. Neural Electromag metic(NEM) field theory is advanced.
Keiji Suzuki,Yukinori Kakazu 대한전자공학회 1992 대한전자공학회 학술대회 Vol.1992 No.10
This paper proposes a new framework of an autonomous and distributed flexible manufacturing system-Multi Client Robot Groups(MCR)-and describes a stochastic learning scheme applied to managerial problems of the system. The MCR is composed of groups of manufacturing robots, named Client Robots(CRs), which are capable of both versatility and independence in their performances. The MCR is expected to have high performance because the MCR can perform concurrent and corporative processing. However, the system performance is determined by the organizations of the CR groups. Therefore the treatment of the managerial problems and organizations of the system are important problems. In this paper, it is assumed that CR groups being able to processing tasks are selected stochastically based on the strengths of the robot groups. The learning scheme adjusting the strength is introduced to organize the groups in the system and control the each performance of the groups according to the total system performance. Finally, some experimental results of the learning scheme are shown.
An Approach to the Interactive Design Process Using Genetic Algorithms
Taku OKUNO,Yukinori KAKAZU 대한전자공학회 1992 대한전자공학회 학술대회 Vol.1992 No.10
This paper is aiming to apply the Genetic Algorithms(GAs) to the interactive design. For that purpose, the scheme for utilizing the past design processes for the next interactive design process is proposed. In this scheme, the process consists of three phases: the searching phase, the tuning phase and the design phase. The first phase searches the optimal decision sequences for the past design instances by GAs. By the collected sequences, the second phase tunes the criteria of selecting decision sequences for the next design process. By this scheme, the implicit constraints satisfied in the past design can be applied to the next design. Finally, the computer simulations on the simple gear-train design were carried out to show the effectiveness of the scheme.