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    • 15. 发明授权
    • Process of processing silver halide photographic material and
photographic processing composition having a fixing ability
    • 处理卤化银照相材料和具有定影能力的照相处理组合物的方法
    • US5338648A
    • 1994-08-16
    • US127091
    • 1993-09-27
    • Tetsuro KojimaNobuo Watanabe
    • Tetsuro KojimaNobuo Watanabe
    • G03C5/38G03C7/42
    • G03C5/38G03C7/42
    • A process and composition for processing a silver halide photographic material. The photographic material mat be a black and white photographic material or a color photographic material. The photographic material is processed in a photographic processing bath containing at least one compound represented by the following formula (I) and substantially not containing a thiosulfate ion: ##STR1## wherein Q represents an atomic group necessary for forming a 5- or 6-membered heterocyclic ring, which heterocyclic ring may be condensed with a carbon aromatic ring or a hetero-aromatic ring; R represents an alkyl group, an alkenyl group, an aralkyl group, an aryl group or a heterocyclic group, each group represented by R being substituted by at least one substituent selected from the group consisting of a carboxyl group or salt thereof a sulfonic acid group or salt thereof a phosphonic acid group or salt thereof, an amino group and an ammonium group, or R represents a single bond; n represents an integer or from 1 to 3; and M represents a cation group.
    • 用于处理卤化银照相材料的方法和组合物。 照相材料垫是黑色和白色照相材料或彩色照相材料。 照相材料在含有至少一种由下式(I)表示的化合物并且基本上不含有硫代硫酸根离子的照相处理浴中进行处理:其中Q表示形成5-或 6元杂环,该杂环可以与碳芳环或杂芳环稠合; R表示烷基,烯基,芳烷基,芳基或杂环基,R表示的基团被至少一个选自羧基或其盐的磺酸基取代基取代 或其盐,膦酸基或其盐,氨基和铵基,或R表示单键; n表示1〜3的整数, M表示阳离子基团。
    • 16. 发明授权
    • Learning process system for use with a neural network structure data
processing apparatus
    • 用于神经网络结构数据处理装置的学习过程系统
    • US5333239A
    • 1994-07-26
    • US3856
    • 1993-01-11
    • Nobuo WatanabeTakashi KimotoAkira KawamuraRyusuke MasuokaKazuo Asakawa
    • Nobuo WatanabeTakashi KimotoAkira KawamuraRyusuke MasuokaKazuo Asakawa
    • G06N3/04G06N3/08G06F15/18G06G7/60
    • G06N3/084G06N3/04
    • A learning process system is provided for a neural network. The neural network is a layered network comprising an input layer, an intermediate layer and an output layer formed of basic units. In the basic units, a plurality of inputs is multiplied by a weight signal and the products are accumulated, thereby supplying the sum of products. An output signal is obtained using a threshold value function in response to the sum of products. An error signal is generated by an error circuit in response to a difference between the output signal obtained from the output layer and a teacher signal. A weight updating signal is determined in a weight learning circuit by obtaining a weight value in which the sum of the error values falls within an allowable range. Thus, the learning is performed in the layered neural network through use of a back propagation method. Through such learning in the layered neural network, an updating quantity to be obtained in the present weight updating cycle is determined in response to a once delayed weight updating quantity signal in a previous weight updating cycle and a twice delayed weight updating quantity obtained at a twice-previous weight updating cycle prior to the previous weight updating cycle.
    • 为神经网络提供学习过程系统。 神经网络是包括由基本单元形成的输入层,中间层和输出层的分层网络。 在基本单位中,将多个输入乘以权重信号,并积累乘积,从而提供乘积之和。 使用响应于乘积之和的阈值函数获得输出信号。 响应于从输出层获得的输出信号和教师信号之间的差异,误差电路产生误差信号。 在权重学习电路中通过获得误差值之和落在容许范围内的权重值来确定权重更新信号。 因此,通过使用反向传播方法在分层神经网络中进行学习。 通过在分层神经网络中的这种学习,响应于先前权重更新周期中的一次延迟加权更新量信号和在两次延迟加权更新量中获得的当前权重更新周期中将获得的更新量 在先前权重更新周期之前的前一权重更新周期。
    • 18. 发明授权
    • Learning system for a data processing apparatus
    • 一种数据处理设备的学习系统
    • US5297237A
    • 1994-03-22
    • US913749
    • 1992-07-17
    • Ryusuke MasuokaNobuo WatanabeTakashi KimotoAkira KawamuraKazuo AsakawaJun'ichi Tanahashi
    • Ryusuke MasuokaNobuo WatanabeTakashi KimotoAkira KawamuraKazuo AsakawaJun'ichi Tanahashi
    • G06N3/08G06F15/18
    • G06N3/08
    • A learning system is used in a data processing apparatus for learning an input pattern by obtaining an internal-state value necessary for realizing a desired data conversion by performing a pattern conversion defined by the internal-state value and calculating an output pattern corresponding to the input pattern. The learning system comprises a pattern presenting unit for presenting an input pattern group of the subject to be learned for pattern conversion, dividing the input pattern group of the subject to be learned into at least two sets, selecting one of the divided sets, presenting the input pattern group of the selected set to a pattern conversion unit and presenting an input pattern group belonging to all the sets presented up to the current point when the internal-state value to be converged is obtained in accordance with the presentation of the selected set, and an error value calculating unit for calculating an error value representing a magnitude of a non-consistency between an output pattern group outputted in accordance with the presentation and a teacher pattern group representing a pattern to be obtained by the output pattern group.
    • 在用于学习输入模式的数据处理装置中使用学习系统,通过执行由内部状态值定义的模式转换来获得实现所需数据转换所需的内部状态值,并计算与输入对应的输出模式 模式。 该学习系统包括:图案呈现单元,用于呈现要被学习的图案转换的对象的输入图案组,将要学习的被摄体的输入图案组划分为至少两组;选择一个分割组, 根据所选择的集合的呈现,获得所选集合的输入模式组到模式转换单元,并且呈现属于当前点所呈现的所有集合的输入模式组,当满足内部状态值时, 以及误差值计算单元,用于计算表示根据呈现输出的输出图案组与表示由输出图案组获得的图案的教师图案组之间的不一致性的大小的误差值。