Neuroprose Paper: Classifiers on Relatively Compact Sets
Ajit Dingankar
ajit at uts.cc.utexas.edu
Fri Feb 24 14:01:39 EST 1995
**DO NOT FORWARD TO OTHER GROUPS**
Sorry, no hardcopies available.
URL:
ftp://archive.cis.ohio-state.edu/pub/neuroprose/dingankar.relcompact-class.ps.Z
BiBTeX entry:
@ARTICLE{atd17,
AUTHOR = "Sandberg, I. W. and Dingankar, A. T.",
TITLE = "{Classifiers on Relatively Compact Sets}",
JOURNAL = "IEEE Transactions on Circuits
and Systems-I: Fundamental Theory and Applications",
VOLUME = {42},
NUMBER = {1},
PAGES = {57},
YEAR = "1995",
MONTH = "January",
ANNOTE = "",
LIBRARY = "",
CALLNUM = ""
}
Classifiers on Relatively Compact Sets
--------------------------------------
Abstract
The problem of classifying signals is of interest in several
application areas. Typically we are given a finite number $m$ of
pairwise disjoint sets $C_1, \ldots, C_m$ of signals, and we would
like to synthesize a system that maps the elements of each $C_j$ into
a real number $a_j$, such that the numbers $a_1,\ldots,a_m$ are
distinct. In a recent paper it is shown that this classification can
be performed by certain simple structures involving linear functionals
and memoryless nonlinear elements, assuming that the $C_j$ are compact
subsets of a real normed linear space. Here we give a similar
solution to the problem under the considerably weaker assumption that
the $C_j$ are relatively compact and are of positive distance from
each other. An example is given in which the $C_j$ are subsets of $
\Lp(a,b), ~1 \le p < \infty $.
More information about the Connectionists
mailing list