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This paper presents
a comprehensive
evaluation of the
different
multiplication
algorithms and
parallel multiplier
structures for the
design of scalable
multiplication units
to be incorporated
into hardware
components.
Traditional
Arithmetic Logic
Units of digital
computers and
Application Specific
Integrated Circuits
have had to deal
with more than
one, different data
representation
formats. Arithmetic
processes use fixed
length small bit
multipliers while
cryptographic
applications and
graphics
applications use
wide bit multipliers.
Selection of
multipliers for a
particular
application
involves
comparison of
accuracy, speed ,
area, power and
scalability. We
implemented the
algorithmic and
structural based
multipliers using
VHDL in FPGAs
and the
observations give a
comprehensive idea
for selection.

scalable multiplication units
to be incorporated into
hardware components.
Traditional Arithmetic Logic
Units of digital computers
and

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MULTISPECTRAL
CLASSIFICATION OF IRS-
P6 IMAGES USING
TEXTURAL FEATURES
TRAINED SUPERVISED
NEURAL NETWORKS
ABSTRACT Supervised
classification plays an
important role in remote
sensing image
interpretation, in which the
image pixels are classified
to various predefined
categories based on the
spectral reflectance values
in different bands. In
reality some classes have
very close spectral
reflectance values and
therefore they overlap in
the feature space. This
produces spectral
confusion among the
classes and results in
inaccurate classified
images. To remove

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