公开(公告)号：EP0484911A3

公开(公告)日：1994-02-09

申请号：EP91118922.3

申请日：1991-11-06

申请人： SONY CORPORATION

发明人： Tani, Jun

IPC分类号： B25J9/18 ,  B25J9/16

CPC分类号： B25J9/161 ,  B25J9/1664 ,  Y10S706/903

摘要： A signal processing method for efficiently searching an optimum solution in a neural network by including a term of a nonlinear resistance in an equation of motion and changing such nonlinear resistance periodically. According to the method, the range of absolute values of connection weigths between units in the neural network is limited by the equation of motion, hence preventing a prolonged search time that may otherwise be caused by excessive extension of the search scope beyond the requisite. A plurality of patterns are previously embedded or stored in the neural network and, upon input of a predetermined key pattern, the nonlinear resistance is changed periodically to recall a pattern similar to the key pattern, whereby any desired pattern can be searched or retrieved with rapidity and facility out of the complicated patterns. A process of calculating the next position of an articulated robot (12) corresponding to an optimum solution is repeated while periodically changing a nonlinear resistance included in another equation of the positional energy of the robot (12), thereby acquiring the data of the robot path up to a desired goal.

摘要翻译： 一种信号处理方法，用于通过在运动方程中包括非线性电阻的项并周期性地改变这种非线性电阻来有效地搜索神经网络中的最优解。 根据该方法，神经网络中各单元之间的连接权重的绝对值的范围受到运动方程的限制，因此防止了可能由搜索范围的过度扩展超出必要条件而导致的延长的搜索时间。 多个模式预先嵌入或存储在神经网络中，并且在输入预定的键模式时，非线性电阻周期性地改变以调用类似于键模式的模式，由此可以快速地搜索或检索任何期望的模式 并摆脱复杂的模式。 通过周期性地改变包含在机器人（12）的位置能量的另一方程中的非线性电阻，重复计算对应于最优解的多关节机器人（12）的下一个位置的过程，由此获取机器人路径的数据 达到预期的目标。

公开(公告)号：EP0484911B1

公开(公告)日：1998-01-14

申请号：EP91118922.3

申请日：1991-11-06

申请人： SONY CORPORATION

发明人： Tani, Jun

IPC分类号： B25J9/18 ,  B25J9/16

CPC分类号： B25J9/161 ,  B25J9/1664 ,  Y10S706/903

公开(公告)号：EP0484911A2

公开(公告)日：1992-05-13

申请号：EP91118922.3

申请日：1991-11-06

申请人： SONY CORPORATION

发明人： Tani, Jun

IPC分类号： B25J9/18 ,  B25J9/16

CPC分类号： B25J9/161 ,  B25J9/1664 ,  Y10S706/903

摘要： A signal processing method for efficiently searching an optimum solution in a neural network by including a term of a nonlinear resistance in an equation of motion and changing such nonlinear resistance periodically. According to the method, the range of absolute values of connection weigths between units in the neural network is limited by the equation of motion, hence preventing a prolonged search time that may otherwise be caused by excessive extension of the search scope beyond the requisite. A plurality of patterns are previously embedded or stored in the neural network and, upon input of a predetermined key pattern, the nonlinear resistance is changed periodically to recall a pattern similar to the key pattern, whereby any desired pattern can be searched or retrieved with rapidity and facility out of the complicated patterns. A process of calculating the next position of an articulated robot (12) corresponding to an optimum solution is repeated while periodically changing a nonlinear resistance included in another equation of the positional energy of the robot (12), thereby acquiring the data of the robot path up to a desired goal.

摘要翻译： 一种信号处理方法，用于通过在运动方程式中包括非线性电阻项并且周期性地改变这种非线性电阻来有效地搜索神经网络中的最优解。 根据该方法，神经网络中的单元之间的连接重量的绝对值的范围受到运动方程的限制，因此可以防止延长的搜索时间，否则可能由于搜索范围超出必要条件而引起。 多个图案预先嵌入或存储在神经网络中，并且在输入预定键图案时，非线性电阻被周期性地改变以调用类似于键图案的图案，由此可以快速地搜索或检索任何期望的图案 并设置出复杂的模式。 重复对应于最优解的关节式机器人（12）的下一个位置的计算过程，同时周期性地改变机器人（12）的位置能量的另一方程式中包括的非线性电阻，从而获取机器人路径的数据 达到所期望的目标。