Tham khảo tài liệu 'artificial mind system – kernel memory approach - tetsuya hoya part 8', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 66 4 The Self-Organising Kernel Memory SOKM cnt 3 K1 exp - x 3 - CilH ơ2 Sk K2 exp - x 3 - C21 2 2 Sk . Thus since there is no kernel excited by the input x 3 add a new kernel K3 with c3 x 3 and n3 1 . cnt 4 K1 exp - x 4 - CilH ơ2 Sk K exp - x 4 - C2 2 ơ2 Sk K3 exp - x 4 - C3 2 ơ2 Sk Thus again since there is no kernel excited by x 4 add a new kernel K4 with c4 x 4 and n4 0 Terminated. Then it is straightforward that the above four input patterns can be correctly classified by following the procedure in Summary of Testing the Self-Organising Kernel Memory given earlier. In the above on first examination constructing the SOKM takes similar steps for a PNN GRNN since there are four identical Gaussian kernels or RBFs in a single network structure as described in Sect. and by regarding ni i 1 2 3 4 as the target values. Therefore it is also said that PNNs GRNNs are subclasses of the SOKM. However consider the situation where another set of input data which again represent the XOR patterns . x 5 T x 6 T x 7 and x 8 T is subsequently presented during the construction of the SOKM. Then despite all these patterns also being stored in general training schemes of PNNs GRNNs such redundant addition of kernels does not occur during the SOKM construction phase these four patterns excite only the respective nearest kernels due to the criterion all of which nevertheless yield the correct pattern classification results and thus there are no further additional kernels. In other words this excitation evaluating process is viewed as testing of the SOKM. Therefore from this observation it is considered that by exploiting the local memory representation the SOKM acts as a pattern classifier which can simultaneously perform data pruning or clustering with proper parameter settings. In the next couple of simulation examples the issue of the actual parameter setting for the SOKM is discussed further. .
