Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Generation of unpredictable time series by a Neural Network   A perceptron that learns the opposite of its own output is used to generate a
time series. We analyse properties of the weight vector and the generated
sequence, like the cycle length and the probability distribution of generated
sequences. A remarkable suppression of the autocorrelation function is
explained, and connections to the Bernasconi model are discussed. If a
continuous transfer function is used, the system displays chaotic and
intermittent behaviour, with the product of the learning rate and amplification
as a control parameter.

16
The categories of this paper are: stat
8
The categories of this paper are: hep-ex
31
The categories of this paper are: ao-sci
19
The categories of this paper are: eess
29
The categories of this paper are: funct-an
24
The categories of this paper are: dg-ga
27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg
37
The categories of this paper are: supr-con
12
The categories of this paper are: nucl-th
10
The categories of this paper are: q-bio
32
The categories of this paper are: atom-ph
3
The categories of this paper are: physics
33
The categories of this paper are: plasm-ph
21
The categories of this paper are: adap-org
14
The categories of this paper are: math-ph