Patent ID: 7296005

Claim:
A learning apparatus for learning time series data, the learning apparatus comprising: learning means for updating, in a self-organizing manner based on an observed value of the time series data, a time series pattern storage network including a plurality of nodes, each node having a time series pattern model representing a time series pattern of the time series data; wherein the learning means further comprises: a weight determining unit for determining a weight of the node, the weight representing the degree of influence of an observed value of the time series data on the time series pattern model when the time series pattern model of the node is updated, a winner node determining unit for determining, as a winner node, the node most appropriately matching the observed value of the time series data, from among the plurality of nodes forming the time series pattern storage network; and model updating means for updating the time series pattern model of the winner node in accordance with the observed value of the time series data, wherein the model updating means updates the time series pattern model of the winner node and the time series pattern model of the node other than the winner node, based on the observed value of the time series data and the weight, wherein the weight determining unit determines the weight of the node in response to the relationship of the weight and the distance where the weight decreases as the distance increases, and wherein the relationship of the weight and the distance is that a rate of change of the weight increases as the number of updates of the time series pattern model increases.