MAGNETIC DISK DEVICE AND CONTROL METHOD THEREOF, AND INFORMATION PROCESSOR
    1.
    发明申请
    MAGNETIC DISK DEVICE AND CONTROL METHOD THEREOF, AND INFORMATION PROCESSOR 有权
    磁条设备及其控制方法及信息处理器

    公开(公告)号:US20110188154A1

    公开(公告)日:2011-08-04

    申请号:US12876941

    申请日:2010-09-07

    IPC分类号: G11B5/596

    CPC分类号: G11B5/596

    摘要: 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.

    摘要翻译: 根据一个实施例,磁盘装置被配置为使用磁头从磁盘读取数据并向磁盘写入数据,并设置有根据初始固件控制磁盘装置的初始操作的控制模块。 磁盘装置包括读取器,保持器,阻挡器和开关。 读取器读取存储在磁盘中的控制固件。 在读取控制固件之后,保持器固定用于磁头的伺服控制量,并将磁头保持在磁盘上方的预定位置。 阻塞块将中断信号的输入阻塞到控制模块。 在伺服控制量固定并且中断信号的输入被阻塞之后,开关将初始固件切换到控制固件。

    Magnetic disk device and control method thereof, and information processor
    2.
    发明授权
    Magnetic disk device and control method thereof, and information processor 有权
    磁盘装置及其控制方法以及信息处理器

    公开(公告)号:US08693130B2

    公开(公告)日:2014-04-08

    申请号:US12876941

    申请日:2010-09-07

    IPC分类号: G11B21/02 G11B27/26

    CPC分类号: G11B5/596

    摘要: 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.

    摘要翻译: 根据一个实施例,磁盘装置被配置为使用磁头从磁盘读取数据并向磁盘写入数据,并设置有根据初始固件控制磁盘装置的初始操作的控制模块。 磁盘装置包括读取器,保持器,阻挡器和开关。 读取器读取存储在磁盘中的控制固件。 在读取控制固件之后,保持器固定用于磁头的伺服控制量,并将磁头保持在磁盘上方的预定位置。 阻塞块将中断信号的输入阻塞到控制模块。 在伺服控制量固定并且中断信号的输入被阻塞之后,开关将初始固件切换到控制固件。

    Server apparatus, network system and data transmission/reception control method
    3.
    发明申请
    Server apparatus, network system and data transmission/reception control method 审中-公开
    服务器装置,网络系统和数据发送/接收控制方法

    公开(公告)号:US20050094198A1

    公开(公告)日:2005-05-05

    申请号:US10958601

    申请日:2004-10-06

    申请人: Yasushi Ishizuka

    发明人: Yasushi Ishizuka

    CPC分类号: H04L67/125

    摘要: 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.

    摘要翻译: 客户端 - 客户端数据发送/接收控制单元通过使用数据管理列表来检查由客户端装置请求的数据的存储位置。 如果数据存储在不同的客户端设备中,则通过使用客户端设备信息来检查两个客户端设备是否支持直接发送/接收数据的功能。 如果该功能由两个客户端装置支持,则客户端 - 客户端数据发送/接收控制单元向两个客户端装置发出指示,以便在不经过服务器装置的情况下在相关客户机之间进行数据发送/接收。

    Character recognition device which divides a single character region
into subregions to obtain a character code
    4.
    发明授权
    Character recognition device which divides a single character region into subregions to obtain a character code 失效
    字符识别装置,其将单个字符区域划分成子区域以获得字符代码

    公开(公告)号:US5271068A

    公开(公告)日:1993-12-14

    申请号:US871075

    申请日:1992-04-20

    摘要: 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.

    摘要翻译: 字符识别装置具有分割器,特征计算器和字符代码识别装置。 从扫描的字符图像数据中提取单个字符区域的图像数据并输入到分割器。 该分割器将单个字符区域的图像数据划分为子区域。 特征计算器基于子区域中的模板和图像数据之间的相似程度,计算每个子区域中的量化特征。 当针对构成单个字符区域的所有子区域计算每个子区域的特征时,基于每个子区域的量化特征,由字符代码识别装置识别与扫描的字符图像数据相对应的字符代码。

    Recognizing apparatus
    5.
    发明授权
    Recognizing apparatus 失效
    识别装置

    公开(公告)号:US5119438A

    公开(公告)日:1992-06-02

    申请号:US491039

    申请日:1990-03-09

    摘要: 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. The network setting portion sets the structure and weights of a neural network selected by the network selecting portion and a discriminating alogrithm appropriate to the selected category. The details discriminating portion recognizes the class to which the inputted characteristic pattern belongs by performing the details discriminating operation using the neural network set by the neural network setting portion.

    摘要翻译: 提供一种识别装置,用于使用神经网络识别要被区分的多个类别中输入的特征模式所属的类别。 这些课程分为多个类别。 该装置包括网络选择部分,用于选择输入的特征模式所属的类别,并用于选择神经网络以用于区分所选类别中输入的特征模式所属的类别。 该装置还包括网络存储器部分,网络设置部分和细节鉴别部分。 网络存储器部分存储已经完成各种类别的学习的多个神经网络的结构,通过学习设置的神经网络的权重以及当神经网络识别类时要使用的多个鉴别算法。 网络设置部分设置由网络选择部分选择的神经网络的结构和权重以及适合于所选类别的识别算法。 细节识别部分通过使用由神经网络设置部分设置的神经网络执行细节识别操作来识别所输入的特征模式所属的类别。

    CHARACTER INPUT DEVICE, SYSTEM, AND CHARACTER INPUT CONTROL METHOD
    6.
    发明申请
    CHARACTER INPUT DEVICE, SYSTEM, AND CHARACTER INPUT CONTROL METHOD 审中-公开
    字符输入装置,系统和字符输入控制方法

    公开(公告)号:US20100283736A1

    公开(公告)日:2010-11-11

    申请号:US12810273

    申请日:2008-12-26

    IPC分类号: G06F3/02

    摘要: 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. In this manner, in the character input device (5), an input candidate with high probability is assigned to the candidate selection key, allowing a user to easily and swiftly input characters.

    摘要翻译: 字符输入装置(5)(i)基于输入位置之前的字符串确定作为要在输入位置输入的字符串的输入候选,(ii)使显示画面显示候选选择 确定的输入候选者以允许用户选择候选选择密钥的方式被分配的密钥,以及(iii)当选择显示的候选选择密钥时,在输入位置输入输入候选的字符串 分配给所选候选选择键的字符输入装置,包括用于将候选选择键分配Caps键的第一候选确定部分(38),用于将候选选择键分配完成键的第二候选确定部分(39) ,以及用于将候选选择键分配清除键的编辑候选确定部分(40)。 这允许以高概率确定输入候选。 以这种方式,在字符输入装置(5)中,向候选选择键分配具有高概率的输入候选,允许用户容易地并且迅速地输入字符。

    Neural network learning apparatus and method
    7.
    发明授权
    Neural network learning apparatus and method 失效
    神经网络学习装置及方法

    公开(公告)号:US5276769A

    公开(公告)日:1994-01-04

    申请号:US924585

    申请日:1992-08-06

    IPC分类号: G06K9/66 G06N3/08 G06F15/18

    CPC分类号: G06K9/6272 G06N3/08

    摘要: 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. If the determined ratio is smaller than a predetermined value, the weighted first and second largest output vectors are further weighted to be made further larger and smaller, respectively.

    摘要翻译: 一种用于神经网络系统的学习装置,其具有表示不同含义的多个类别。 提供学习装置,用于学习由输入向量输入并分类为不同类别的多个不同模式。 学习装置由计算机构成,它包括一个部分,用于响应于输入向量产生表示不同类别的多个输出向量,用于获得所有输出向量的第一最大输出向量的部分, 所有输出向量的第二大输出向量,以及用于分别对第一和第二最大输出向量设置预定权重的部分,使得第一最大输出向量变大,并且使第二大输出向量更小。 此外,包括分别用于确定加权的第一和第二最大输出向量的比率的部分。 如果确定的比率小于预定值,则加权的第一和第二最大输出向量进一步被加权以进一步越来越大。

    Character recognition device which divides a single character region
into subregions to obtain a character code
    8.
    发明授权
    Character recognition device which divides a single character region into subregions to obtain a character code 失效
    字符识别装置,其将单个字符区域划分成子区域以获得字符代码

    公开(公告)号:US5151951A

    公开(公告)日:1992-09-29

    申请号:US667340

    申请日:1991-03-11

    IPC分类号: G06K9/46 G06K9/66

    CPC分类号: G06K9/4642 G06K2209/01

    摘要: 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.

    摘要翻译: 字符识别装置具有分割器,特征计算器和字符代码识别装置。 从扫描的字符图像数据中提取单个字符区域的图像数据并输入到分割器。 该分割器将单个字符区域的图像数据划分为子区域。 特征计算器基于子区域中的模板和图像数据之间的相似程度,计算每个子区域中的量化特征。 当针对构成单个字符区域的所有子区域计算每个子区域的特征时,基于每个子区域的量化特征,由字符代码识别装置识别与扫描的字符图像数据相对应的字符代码。

    Server apparatus, client apparatus, and communication control method
    9.
    发明申请
    Server apparatus, client apparatus, and communication control method 审中-公开
    服务器装置,客户端装置和通信控制方法

    公开(公告)号:US20050265295A1

    公开(公告)日:2005-12-01

    申请号:US11137366

    申请日:2005-05-26

    申请人: Yasushi Ishizuka

    发明人: Yasushi Ishizuka

    摘要: 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.

    摘要翻译: 接入点确定用于站的无线通信信道,用于直接相互发送和接收数据,并通知每个站点切换到信道的指令。 此后,接入点等待每个站点通知直接数据发送和接收的结束。 另一方面,每个站在接收到切换指令时切换到指定的信道并执行直接的数据发送和接收。 在完成直接数据发送和接收之后,每个站切换到原始信道并通知接入点直接数据发送和接收的结束。 作为其结果,接入点和站重新启动彼此的无线通信。

    Neural network apparatus
    10.
    发明授权
    Neural network apparatus 失效
    神经网络装置

    公开(公告)号:US5283838A

    公开(公告)日:1994-02-01

    申请号:US685596

    申请日:1991-04-15

    CPC分类号: G06K9/6272 G06N3/10

    摘要: 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.

    摘要翻译: 当对神经网络进行学习时,使用属于任意类别的多个学习向量,并且执行该类别中的自组织学习。 结果,属于该类别的多个学习向量被自动聚类,将神经网络中权重向量的内容设置为表示每个簇的学习向量的共同特征的代表向量。 然后,对神经网络进行教师监督学习,使用这样设定的权重向量的内容作为其初始值。 在学习过程中,将每个权重向量的初始值设置为通过聚类获得的每个簇的代表向量。 因此,在教师监督学习融合之前所需的计算量大大减少。