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    • 26. 发明专利
    • NEURON NETWORK DEVICE
    • JPH03232078A
    • 1991-10-16
    • JP2916090
    • 1990-02-07
    • MITSUBISHI ELECTRIC CORP
    • IZUI YOSHIO
    • G06G7/60G06F15/18G06N3/04G06N99/00
    • PURPOSE:To facilitate integration and to simulate the neural system of a living body by coupling arithmetic units into meshes and allowing respective arithmetic units to simulate the neural system of the living body while communicating with one another in two directions. CONSTITUTION:A communication line 13 capable of communication in two directions connects upper, lower, left, and right, arithmetic units 12 to constitute meshes of an operation network. All arithmetic units 12 synchronously execute the same instruction through a control command line 15 by the control instruction from a host computer 14. Internal states and output values of neural elements obtained by simulating neural cells of the living body by respective arithmetic units 12 and coupling weights which simulate synapses between neural elements are stored in a memory, and mutual communication of arithmetic units 12 is controlled by a controller to simulate the neural system of the living body. Thus, the device is easily arranged on a plane and is easily integrated, and the neural system of the living body is simulated at a high body.
    • 27. 发明专利
    • COMMAND VALUE DETERMINING DEVICE
    • JPH10254503A
    • 1998-09-25
    • JP5213897
    • 1997-03-06
    • MITSUBISHI ELECTRIC CORP
    • TANIMOTO MASAHIKOIZUI YOSHIO
    • G05B13/04
    • PROBLEM TO BE SOLVED: To precisely determine output command values of respective plants which minimize the fuel consumptions of the respective plants by extracting items affecting the current fuel consumptions from fuel consumption characteristic model of the respective plants that are determined in consideration of history characteristics and generating output decision models of the respective plants. SOLUTION: A fuel consumption characteristic model generation part 5 gathers data on fuel consumption Qm for outputs Pm of the plants by the plants Gm which are mutually connected and generates fuel consumption characteristic models Fm ,t in consideration of history characteristics. A storage part 6 stores the generated fuel consumption characteristic models Fm ,t and output decision models Hm ,t generated by an output decision model generation part 7. The output decision model generation part 7 extracts items affecting the fuel consumptions Qm ,t0 at current time t0 from fuel consumption characteristic models Fm ,t regarding the respective plants Gm and generate output decision models Hm ,t0 of the respective plants Gm .