Mitsubishi Denki Kabushiki Kaisha

Mitsubishi Electric Corporation

Kazuo Kyuma

Shuichi Tai

Masaya Oita

Masanobu Takahashi

Jun Ohta

Keisuke Kojima

Masahiro Yamaguchi

Nagaaki Ohyama

Kunihiko Hara

Susumu Noda

Eiichi Funatsu

Yoshikazu Nitta

Takashi Toyoda

Toshio Shinnishi

Hiroaki Sugiura

Jun Someya

Kazuhiko Tsutsumi

Shinji Komori

Akihiro Takeda

Hironobu Yasui

Hiroshi Kage

Toshinao Ishii

Yuichi Koshiba

Wei Zhang

Eberhard Lange

Masaaki Kameya

Koichi Hammanaka

A video display apparatus generates luminance information for individual frames of a video signal from histograms of the luminance component of the video signal, and classifies the content of the video signal on the basis of this information. Color saturation information is also generated from color saturation histograms, and scene changes are detected. Video correction parameters and display control parameters are derived from the content classification and color saturation information. The video signal is corrected according to the video correction parameters, and displayed according to the display control parameters. Display characteristics suitable for the video content are thereby obtained. The parameters are changed when a scene change is detected, so that the viewer is not disturbed by the change in video display characteristics.

Video display apparatus that adjusts video display parameters based on video picture type

An apparatus for inputting information includes an image input section which acquires the image information through an image sensor, a motion calculation section which calculates a distance of movement based on the image information, an information selection section which selects symbol information from a symbol table in operatively interlocked relation with the calculated distance of movement, and an information display section which displays the symbol table and the selected symbol information.

Apparatus for inputting information and computer product

An apparatus for sensing and processing images is provided with a photo detector array arranged in a matrix form, a control circuit for feeding a row of the array with voltage for sensitivity control, and a neural network for processing current flowing from a column of the array to the ground in order to obtain an apparatus for sensing and processing images having a simple configuration, a high frame speed, the capability of forming a focus of attention, and high throughput of data and possibility of connecting to the neural network.

Apparatus and method for sensing and processing images

A learning method for a neural network, in which at least a portion of the interconnection strength between neurons takes discrete values, includes the steps of updating an imaginary interconnection strength taking continuous values by using the quantity of update of the interconnection strength which has been calculated by using the discrete interconnection strength, and discretizing the imaginary interconnection strength so as to provide a novel interconnection strength.

Learning method for neural network having discrete interconnection

The part arrangement optimizing method of the present invention is a part arranging method capable of obtaining part arrangements having smaller evaluation function values rapidly, and the method improves block arrangements so that evaluation function values such as total route lengths become small as much as possible by replacing plural blocks or block sets to determine the arrangements of parts on the basis of the arrangements of the blocks. Furthermore, as aforementioned improving method of the blocks, such a method as assigns expected positional coordinate to each part and arranges a block to a block arranging position near to the expected positional coordinate while renewing the expected positional coordinate so as to be located at the position where the evaluation function value becomes smaller.

Part arrangement optimizing method

An input pattern or two-dimensional pattern is associated and stored with use of associative matrices having the same size as that of an input pattern without converting it into one-dimensional pattern, wherein the associative matrices are generated from the input pattern so as to maximize the Hamming distance between state invariants which correspond to each different storage pattern, and thereby a power of categorization that corresponds to each storage pattern can be enhanced, thus increasing the storage capability and robustness.

Method of storing associative information and a device therefor

A photodetector has a semiconductor substrate which produces light-induced charge upon the absorption of incident light. A first electrode and a second electrode are attached to the surface of the semiconductor substrate so as to form metal-semiconductor junctions. When control voltage V.sub.B, which is variable in a positive range through a negative range, is applied to the first electrode, a photocurrent flows through the second electrode and depletion layers are formed in the surface of the semiconductor substrate. The control voltage V.sub.B applied to the first electrode increases the expanse of one of the depletion layers relative to that of the other to cause the light-induced charge to drift toward one of the depletion layers or the other. Consequently, a positive or negative current is delivered through the second electrode. Thus, the photosensitivity of the photodetector can be controlled by the control voltage V.sub.B.

Photodetector, a photodector array comprising photodetectors, an object

An information retrieval system allowing the user to build a database or to retrieve data therefrom based on vague retrieval-designating data without becoming aware of the database structure. The system comprises a neural network, a memory, an interface part and a CRT. The neural network stores data designating electronic still pictures contained in the memory. When data for designating retrieval are input, the interface part groups the data into such categories as the place where the desired picture was taken and the date on which it was taken, and supplies the neural network with the categorized input data. In turn, the neural network outputs by association the data corresponding to the input data. Given the data from the network, the memory outputs the relevant electronic still picture to the CRT for display.

Information retrieval system

An intelligence information processing system is composed of an associative memory and a serial processing-type computer. Input pattern information is associated with the associative memory, and pattern recognition based on the computer evaluates an associative output. In accordance with this evaluation, an associative and restrictive condition is repeatedly added to the energy function of a neural network constituting the associative memory, thereby converging the associative output on a stable state of the energy. The converged associative output is verified with intelligence information stored in a computer memory. The associative and restrictive condition is again repeatedly added to the energy function in accordance with the verification so as to produce an output from the system.

Intelligence information processing method

A neural network for solving the problem of the optimization of the arrangement of at least two parts which are combined with each other through connecting wires. One neuron is assigned to each part. Each neuron has a synapse with a weight. Weights of the synapses of a neuron are initially set, and a learning process is repeated a while satisfying restricting conditions. In the learning process, the fittest neurons for all the coordinates of the positions at which the parts are disposed are selected in accordance with a predetermined standard while serially updating the weights of the synapses of the neurons so as to satisfy the restricting conditions. After the fittest neurons for all the coordinates of the positions are selected, judgment is made as to whether or not the arrangement obtained in the current learning cycle is closer to an optimal arrangement than any other arrangement which has been obtained in previous learning cycles. The optimal arrangement obtained from a set of learning cycles is provided as an indication of a quasi-optimal arrangement.

Method of optimizing a combination using a neural network

A data processing apparatus having one or more processors each comprising an optical vector matrix multiplier and its peripheral circuits mounted on a single semiconductor substrate, the multiple processors constituting a network. The components of the optical vector matrix multiplier may be divided on two semiconductor substrates so that light-borne data is exchanged therebetween. These arrangements provide a compact multifunction data processing apparatus adapted to deal flexibly with diverse computing problems.

Data processing apparatus with optical vector matrix multiplier and

The knowledge information processing system includes a first and second associative memory unit groups. The associative memory units of the first associative memory unit group 1 associates a plurality of distinct features to the input pattern 20. In response to the combination of associated outputs from the first associative memory unit group 1, the second associative memory unit group 4 evaluates and associates features corresponding to those associated by the first associative memory unit group 1. The logical operation unit group 6 compares the associated outputs of the first associative memory unit group 1 with those of the second to judge whether or not corresponding associated outputs agree with each other. If the corresponding associated outputs do not agree, the logical operation unit group 6 outputs feedback information items for correcting the energy functions of the first associative memory unit group 1, thereby repeating the association and the evaluation process.

Knowledge information processing system including two associative memory

A neural network for solving the problem of the optimization of the arrangement of N (at least two) parts which are combined with each other through connecting wires. After the weights of the synapses of a neuron which is allotted to each part are initially set, a learning process is repeated a predetermined number of times while satisfying restricting conditions. In the learning process, the fittest neurons for all the coordinates of the positions at which the parts are disposed are selected in accordance with a predetermined standard while serially updating the weights of the synapses of the other neurons so as to satisfy the restricting conditions. After the fittest neurons for all the coordinates of the positions are selected, judgement is made as to whether or not the arrangement obtained in the current learning cycle is closer to an optimal arrangement than any other arrangement which has been obtained in previous learning cycles.

Method of optimizing combination by neural network

Intelligence information processing system

An optical computer for performing product and/or sum operations on input vector information and matrix information includes an array of light emitting elements, the array having a plurality of columns and a plurality of rows. Input circuitry is provided for supplying input vector information to the array while matrix circuitry is provided for dynamically applying matrix information to the array. Logic circuitry is provided for performing one of a logical product and a logical sum operation on the input vector information and the matrix information and for generating an output thereof.

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Hyogo, Japan

Kazuo Kyuma