Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Analysis of Bidirectional Associative Memory using SCSNA and Statistical
  Neurodynamics   Bidirectional associative memory (BAM) is a kind of an artificial neural
network used to memorize and retrieve heterogeneous pattern pairs. Many efforts
have been made to improve BAM from the the viewpoint of computer application,
and few theoretical studies have been done. We investigated the theoretical
characteristics of BAM using a framework of statistical-mechanical analysis. To
investigate the equilibrium state of BAM, we applied self-consistent signal to
noise analysis (SCSNA) and obtained a macroscopic parameter equations and
relative capacity. Moreover, to investigate not only the equilibrium state but
also the retrieval process of reaching the equilibrium state, we applied
statistical neurodynamics to the update rule of BAM and obtained evolution
equations for the macroscopic parameters. These evolution equations are
consistent with the results of SCSNA in the equilibrium state.

33
The categories of this paper are: plasm-ph
9
The categories of this paper are: nlin
21
The categories of this paper are: adap-org
10
The categories of this paper are: q-bio
8
The categories of this paper are: hep-ex
35
The categories of this paper are: mtrl-th
24
The categories of this paper are: dg-ga
19
The categories of this paper are: eess
0
The categories of this paper are: hep-ph
27
The categories of this paper are: comp-gas
3
The categories of this paper are: physics
36
The categories of this paper are: cmp-lg
34
The categories of this paper are: chem-ph
29
The categories of this paper are: funct-an
14
The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an