Hitachi, Ltd.

Hitachi-omron Terminal Solutions, Corporation

Hitachi Microcomputer System, Ltd.

Hisao Ogata

Junichi Higashino

Masahiro Abe

Hiroshi Sakou

Hiroyuki Suzuki

Atsushi Kato

Hiromichi Fujisawa

Toshiaki Nakamura

Masaru Ohki

Keisuke Nakashima

Shinichi Shinoda

Shigeru Watanabe

Yoshihiro Shima

Masashi Koga

Tatsuhiko Kagehiro

Kunihiro Nomura

Hiroshi Sako

Mitsuo Asai

Masato Teramoto

Yuji Sato

Akihiro Kawaoka

Yoshiharu Konishi

Katsunari Shibata

Shuuji Tanaka

Takanari Tanabata

Atsuhiro Imaizumi

Tatsuo Okahashi

Keiji Moki

Tomoyoshi Ishikawa

Mitsunari Kanou

Takahiro Sakaguchi

Yasuo Mizuno

Junichi Ozasa

Noboru Takamura

Tatsuo Ochiai

Yoshihiro Kuwabara

Hiroshi Takayanagi

Masashi Hashimoto

Tetsuya Hori

Shuuichi Yamano

Yoshinaga Horii

Norichika Miyamoto

Eiji Makimoto

Shunichi Enomoto

Kouhei Nagata

Provided is a highly reliable automatic transaction apparatus. This automatic transaction apparatus comprises a control unit which generates transaction data related to a transaction, and generates a command for payout, deposit or remittance based on the transaction data, and a first device which detects an abnormality of the control unit based on a command sent from the control unit according to an input from a device that is different from the control unit, wherein the first device sends the command to a second device that is different from the first device when the first device determines that an abnormality of the control unit is not detected based on a command sent from the control unit.

Automatic transaction apparatus

Proposed are a highly reliable automatic transaction device and a control method thereof. Specifically provided is an automatic transaction device, and a control method thereof, including a main body control unit which generates first withdraw transaction data including amount information as information related to an amount in a withdraw transaction and a withdraw command for instructing a withdraw of a paper currency based on the first withdraw transaction data, a paper currency processing unit which receives the withdraw command and pays out the paper currency, and a first device which is a device that is different from the paper currency processing unit and which determines a feasibility of a withdraw based on the first withdraw transaction data sent from the main body control unit. When the first device determines that the withdraw is possible, the first device generates withdraw credit information with security that is higher than the withdraw command based on the first withdraw transaction data. The paper currency processing unit receives the withdraw credit information and the withdraw command, additionally determines the feasibility of the withdraw based on the withdraw credit information and the withdraw command, and pays out the paper currency when the withdraw is possible.

Automatic transaction device and control method thereof

A highly reliable automatic transaction apparatus and control method thereof which are capable of suppressing unauthorized transactions and the like are proposed. A plurality of modules which each execute processing required for the payout transaction, an overall control unit which controls each of the modules, and a security control unit are provided in an automatic transaction apparatus; the security control unit holds in advance a first list in which content of signals which are exchanged between the overall control unit and each of the modules at the time of a normal payout transaction is recorded in the order in which the signals are exchanged, sequentially records the content of the signals which are exchanged between the overall control unit and each of the modules at the time of the actual payout transaction in a second list in the order in which the signals are exchanged, and issues a signature approving operation of the modules when there is a match between the content of the first list and the content of the second list, and the modules execute a corresponding operation when the security control unit has issued the signature.

Automatic transaction apparatus and control method thereof

A biometric authentication apparatus for performing user authentication based on finger/palm print information representing a biological characteristic of fingerprint or palm print and vein information representing a biological characteristic of vein, comprises:

Biometric authentication apparatus and biometric authentication method

A structure holds a medium itself to be scanned flat on an installation base in a stand type image input device. The installation base of the image recognition apparatus is provided with a mechanism which clips a medium and straightens creases and curls in the medium. the installation base may be provided with adhesion. Alternatively a mechanism for holding down a medium with filaments finer than the resolution of the image input device maybe provided.

Form fixing structure and image recognition apparatus having the structure

A simple non-contact image reader of high degree of freedom comprising a reading unit for reading images, a reading condition changing unit for changing the reading conditions of the reading unit, a storage unit for storing two read images which are read under two different reading conditions changed, and an image correction unit for composing two read images stored and developing them on a plane, wherein characters written on the surface of a folded form or a thick book can be read in a good operability state and on a high image quality basis by reading images in non-contact.

Non-contact image reader and system using the same

A character reading method has enhanced character segmentation accuracy and character string recognition accuracy for reading correctly hand-written addresses on postal matters. The method extracts provisional character patterns from image information of the address character string (step,), creates a table,of tentative character patterns and implements the character classification for the tentative character patterns (step,), extracts, specifically for characters of the street number portion of the address character string, periphery information (vertical and horizontal lengths, vertical/horizontal length ratio, pattern spacings, etc.) of tentative character patterns (step,), and segments the character string into characters accurately based on the information (step,).

Method of reading characters and method of reading postal addresses

A general neuro-computer and system using it is capable of executing a plurality of learning algorithms, providing an instruction execution speed comparable with a hard wired system, and practically neglecting a time required for rewriting microprograms. The neuro-computer is constituted by a neuron array having a plurality of neurons, a control storage unit for storing microinstructions, a parameter register, a control logic, and a global memory. A host computer as a user interface inputs information necessary for the learning and execution of the neuro-computer to the system, the information including learning algorithms, neural network architecture, the number of learnings, the number of input patterns, input signals, and desired signals. The information inputted from the host computer is transferred via a SCSI to the neuro-computer to perform a desired neural network operation.

Neuro-computer system for executing a plurality of controlling algorithms

A neural network (100) has an input layer, a hidden layer, and an output layer. The neural network stores weight values which operate on data input at the input layer to generate output data at the output layer. An error computing unit (87) receives the output data and compares it with desired output data from a learning data storage unit (105) to calculate error values representing the difference. An error gradient computing unit (81) calculates an error gradient, i.e. rate and direction of error change. A ratio computing unit (82) computes a ratio or percentage of a prior conjugate vector and combines the ratio with the error gradient. A conjugate vector computing unit (83) generates a present line search conjugate vector from the error gradient value and a previously calculated line search gradient vector. A line search computing unit (95) includes a weight computing unit (88) which calculates a weight correction value. The weight correction value is compared (18) with a preselected maximum or upper limit correction value (.kappa.). The line search computing unit (95) limits adjustment of the weight values stored in the neural network in accordance with the maximum weight correction value.

Learning method and apparatus for neural networks and simulator with

A learning control method reduces overall learning time by displaying data related to an appropriate determination of learning protraction and a proper restoring method. Prior to initiating the learning, the user is inquired about the current problem and a problem data set representing items associated with the problem is obtained. Evaluation data indicating a state of learning obtained during the learning on the current problem is sequentially stored and displayed. When there is a high possibility of learning protraction during the learning, a message informing the user is displayed. When the learning is stopped by the user in this case, the problem data set and evaluation data set are stored. Then, a list of restoring methods is displayed and a particular restoring method is selected by the user once the learning is stopped. The learning is restarted on the current problem in accordance with the selected restoring method.

Method of and system for controlling learning in neural network

Growing community of inventors

Tokyo, Japan

Hisao Ogata