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Self-organization in the SOM with a decreasing neighborhood function of any width

机译:索峰的自我组织,具有任何宽度的邻域函数

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A proof of self-organization for a general one dimensional SOM (i.e., one dimensional array of neurons, one dimensional input) with a strictly monotonically decreasing neighborhood function of any width W is given. The proof is not dependent on any particular type of probability distribution of the input but rather minimum conditions that the distribution must satisfy are specified. For a total of N neurons the degree (n) of the SOM is defined here as n=N div W+1 when N mod W/spl ne/0 or else n=N/W. It is shown that a total of 2/sup n/ intervals of nonzero probability on the support of the input, separated by distances which depend on parameters of the SOM are sufficient for self-organization.
机译:给出了一般尺寸SOM的自组织证明(即,一维神经元阵列,一维输入),其具有严格单调地降低任何宽度W的邻域函数。证据不依赖于输入的任何特定类型的概率分布,而是指定了分布必须满足的最小条件。对于总共n神经元,当n mod w / spl ne / 0或n = n / w时,这里定义SOM的程度(n)在此定义为n = n div w + 1。结果表明,通过依赖于SOM参数的距离分开的输入上的总共2 / sup n /间隔,其依赖于SOM的参数足以进行自组织。

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