Abstract: According to one embodiment, a magnetic disk device is configured to read data from and write data to a magnetic disk using a magnetic head and provided with a control module that controls initial operation of the magnetic disk device according to initial firmware. The magnetic disk device includes a reader, a retainer, a blocker, and a switch. The reader reads control firmware stored in the magnetic disk. The retainer fixes a servo control amount for the magnetic head after the control firmware is read, and retains the magnetic head at a predetermined position above the magnetic disk. The blocker blocks input of an interrupt signal to the control module. The switch switches the initial firmware to the control firmware after the servo control amount is fixed and the input of an interrupt signal is blocked.

Abstract: According to one embodiment, a magnetic disk device is configured to read data from and write data to a magnetic disk using a magnetic head and provided with a control module that controls initial operation of the magnetic disk device according to initial firmware. The magnetic disk device includes a reader, a retainer, a blocker, and a switch. The reader reads control firmware stored in the magnetic disk. The retainer fixes a servo control amount for the magnetic head after the control firmware is read, and retains the magnetic head at a predetermined position above the magnetic disk. The blocker blocks input of an interrupt signal to the control module. The switch switches the initial firmware to the control firmware after the servo control amount is fixed and the input of an interrupt signal is blocked.

Abstract: The character input device (5) (i) determines an input candidate that is a character string to be inputted at an input position on a basis of a character string before the input position, (ii) causes a display screen to display a candidate selection key to which the determined input candidate is assigned in such a manner as to allow a user to select the candidate selection key, and (iii) when the displayed candidate selection key is selected, inputs at the input position the character string of the input candidate assigned to the selected candidate selection key, the character input device including a first candidate determination section (38) for assigning a Caps key to the candidate selection key, a second candidate determination section (39) for assigning a Done key to the candidate selection key, and an editing candidate determination section (40) for assigning a Clear key to the candidate selection key. This allows determining an input candidate with high probability.

Abstract: An access point determines a wireless communication channel used for stations to transmit and receive data directly to and from each other and informs each of the stations of an instruction to switch to the channel. Thereafter, the access point waits for each of the stations to give notice of the end of the direct data transmission and reception. On the other hand, each of the stations, when receiving the switch instruction, switches to the specified channel and executes direct data transmission and reception. After finishing the direct data transmission and reception, each of the stations switches to the original channel and informs the access point of the end of the direct data transmission and reception. As a result of this, the access point and the stations restart wireless communication with one another.

Abstract: A client-client data transmission/reception control unit checks the storage location of data requested by a client apparatus by use of a data management list. If the data is stored in a different client apparatus, whether a function of directly transmitting/receiving data is supported by the two client apparatuses is checked by use of client apparatus information. If the function is supported by both of the client apparatuses, the client-client data transmission/reception control unit issues an instruction to the two client apparatuses to make data transmission/reception between the concerned client apparatuses without passing through a server apparatus.

Abstract: There is provided a server apparatus that is connectable to client apparatuses via a radio transmission medium. The server apparatus includes a storage unit storing list data indicating a priority order of the client apparatuses in allocating an exclusive period thereto, the exclusive period being a period in which exclusive use of the radio transmission medium is permitted, a control unit configured to allocate the exclusive period to the client apparatuses in accordance with the priority order indicated by the list data, and a processing unit configured to rearrange the priority order of the client apparatuses on the list data using situation data indicating a situation of one of the client apparatuses, when the situation data is transmitted from the one.

Abstract: A transmitting device is provided with a TV tuner for receiving television broadcasts, a DVD player for reading out data from a DVD medium, etc. Based on the wireless communications between the transmitting device and the user's small terminal carried by the user, the ID of a receiving device that is located in the neighborhood of the user is acquired. The transmitting device 1 transfers a variety kinds of data, including television broadcast data received by the TV tuner and the DVD data read out by the DVD player, to the recognized receiving device identified by the ID received from the user's small terminal.

Abstract: When performing learning for a neural network, a plurality of learning vectors which belong to an arbitrary category are used, and self-organization learning in the category is carried out. As a result, the plurality of learning vectors which belong to the category are automatically clustered, and the contents of weight vectors in the neural network are set to representative vectors which exhibit common features of the learning vectors of each cluster. Then, teacher-supervised learning is carried out for the neural network, using the thus set contents of the weight vectors as initial values thereof. In the learning process, an initial value of each weight vector is set to the representative vector of each cluster obtained by clustering. Therefore, the number of calculations required until the teacher-supervised learning is converged is greatly reduced.

Abstract: A learning apparatus for use in a neural network system which has a plurality of classes representing different meanings. The learning apparatus is provided for learning a number of different patterns, inputted by input vectors, and classified in different classes. The learning apparatus is constructed by a computer and it includes a section for producing a plurality of output vectors representing different classes in response to an input vector, a section for obtaining a first largest output vector of all the output vectors, a section for obtaining a second largest output vector of all the output vectors, and a section for setting predetermined weights to the first and second largest output vectors, respectively, such that the first largest output vector is made larger, and the second largest output vector is made smaller. Furthermore, a section for determining a ratio of the weighted first and second largest output vectors, respectively, is included.

Abstract: A character recongintion device has a subdivider, a features calculator and a character code recognition device. Image data for a single character area is extracted from scanned character image data and input to the subdivider. This subdivider divides the image data for the single character area into subregions. The features calculator calculates quantified features in each subregion based on a degree of resemblance between a template and image data in the subregions. When the features of each subregion are calculated for all subregions constituting the single character area, a character code corresponding to the scanned character image data is recognized by the character code recognition device based on the quantified features of each of all subregions.

Abstract: A character recognition device has a subdivider, a features calculator and a character code recognition device. Image data for a single character area is extracted from scanned character image data and input to the subdivider. This subdivider divides the image data for the single character area into subregions. The features calculator calculates quantified features in each subregion based on a degree of resemblance between a template and image data in the subregions. When the features of each subregion are calculated for all subregions constituting the single character area, a character code corresponding to the scanned character image data is recognized by the character code recognition device based on the quantified features of each of all subregions.

Abstract: A recognizing apparatus is provided for recognizing a class to which an inputted characteristic pattern belongs from among a plurality of classes to be discriminated using a neural network. The classes are classified into a plurality of categories. The apparatus includes a network selecting portion for selecting a category to which the inputted characteristic pattern belongs and for selecting a neural network for use in discriminating the class to which the inputted characteristic pattern belongs in the selected category. The apparatus further includes a network memory portion, a network setting portion and a details discriminating portion. The network memory portion stores structures of a plurality of neural networks which have finished learning for respective categories, weights of the neural networks set by the learning and a plurality of discriminating algorithms to be used when the classes are discriminated by the neural networks.

Abstract: A self-extending shape neural-network is capable of a self-extending operation in accordance with the studying results. The self-extending shape neural-network has initially minimum number of the intermediate layers and the number of the nodes (units) within each layer by the self-extension of the network construction so as to shorten the studying time and the discriminating time. This studying may be effected efficiently by the studying being directed towards the focus when the studying is not focused.