Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Convergence of a New Learning Algorithm   A new learning algorithm proposed by Brandt and Lin for neural network [1],
[2] has been shown to be mathematically equivalent to the conventional
back-propagation learning algorithm, but has several advantages over the
backpropagation algorithm, including feedback-network-free implementation and
biological plausibility. In this paper, we investigate the convergence of the
new algorithm. A necessary and sufficient condition for the algorithm to
converge is derived. A convergence measure is proposed to measure the
convergence rate of the new algorithm. Simulation studies are conducted to
investigate the convergence of the algorithm with respect to the number of
neurons, the connection distance, the connection density, the ratio of
excitatory/inhibitory synapses, the membrane potentials, and the synapse
strengths.

15
The categories of this paper are: nucl-ex
26
The categories of this paper are: bayes-an
8
The categories of this paper are: hep-ex
4
The categories of this paper are: cond-mat
24
The categories of this paper are: dg-ga
16
The categories of this paper are: stat
14
The categories of this paper are: math-ph
0
The categories of this paper are: hep-ph
5
The categories of this paper are: gr-qc
12
The categories of this paper are: nucl-th
34
The categories of this paper are: chem-ph
22
The categories of this paper are: chao-dyn
3
The categories of this paper are: physics
36
The categories of this paper are: cmp-lg
11
The categories of this paper are: hep-lat
25
The categories of this paper are: patt-sol