Generating loosely coupled parts by forming couplings between partial nodes in a hierarchical neural network in accordance with a check matrix of an error correcting code.
Please help me write a proper abstract based on the patent claims. CLAIM: 1.-8. (canceled) 9. A hierarchical neural network apparatus comprising: a weight learning processor to learn weights between a plurality of nodes in a hierarchical neural network, the hierarchical neural network being formed by loose couplings between the nodes in accordance with a check matrix of an error correcting code and comprising an input layer, intermediate layer and output layer, each of the layers comprising nodes; and a processor to solve a classification problem or a regression problem using the hierarchical neural network whose weights between the nodes coupled are updated by weight values learned by the weight learning unit. 10. The hierarchical neural network apparatus according to claim 9, wherein the error correcting code is one of codes consisting of a pseudorandom number code, finite geometry code, cyclic code, pseudo-cyclic code, LDPC code and spatially-coupled code. 11. The hierarchical neural network apparatus according to claims 9, further comprising: a weight adjuster to adjust the weights by supervised learning; and wherein the intermediate layer comprising a plurality of layers and the weights between the nodes coupled are updated by weight values adjusted by the weight adjuster. 12. The hierarchical neural network apparatus according to claim 11, wherein the error correcting code is one of codes consisting of a pseudorandom number code, finite geometry code, cyclic code, pseudo-cyclic code, LDPC code and spatially-coupled code. 13. A classifier learning method, which learns a hierarchical neural network comprising an input layer, intermediate layer and output layer, each of the layers comprising nodes, wherein the method comprises: computing a plurality of correction values of weights between a plurality of nodes in the hierarchical neural network, the hierarchical neural network having loose couplings formed in accordance with a check matrix of an error correcting code; and updating weight values between the nodes by the correction values. 14. The classifier learning method according to claim 13, wherein the method further comprises: adjusting the weight values by supervised learning. 15. A discriminating method to make a discrimination using the hierarchical neural network whose weight values between the nodes are updated by the classifier learning method as defined in claim 13. 16. A discriminating method to make a discrimination using the neural network whose weight values between the nodes are updated by the classifier learning method as defined in claim 14.