a neural network model for limb trajectory formation
a neural network model for limb trajectory formation
... coordinate-
transformation problem and proposed an iterative
control learning algorithm. Our research dealt with a
sensory-motor transformation based on a non-
hierarchical layered architecture ...
strategy remains basically the same in both intact and
spinal animals. This result suggests that the basic
motor programs for this particular task are generated
at the spinal cord lev...
Tài liệu Evolving the neural network model for forecasting air pollution time series pdf
... 1996–
1998 was used as training data and data from the year
1999 as model validation data. This approach was
computationally expensive due to long training times of
NN models. However, it was utilised ... the forecasting
point) of a forecasted pollutant, given an input vector
containing earlier air quality measurements at T+0 h
and weather observations at T+24 h (simulating a
weather fo...
designing and implementing a neural network library for handwriting detection, image analysis etc
... INeuronStrategy, called BackPropNeuronStrategy (for a backward propagation neural
network) .
A Neural Network is initialized and connections betweens layers are made by a neural network factory. A Factory
should ... section explains how the training takes place, in a back ward propagation neural network. In a backward
propagation neural network, there are several...
Tài liệu A neural-network-based space-vector PWM controller for a three-level voltage-fed inverter induction motor drive doc
... Therefore,
it appears logical that a feedforward backpropagation-type
ANN which has high computational capability can implement
an SVM algorithm. Note that the ANN has inherent learning
capability ... undermodulation range. A
simulated DSP-based modulator generates the data which are
used to train the network by a backpropagation algorithm in
the MATLAB Neural Network Toolbox. The...
a comparison of neural network architectures for
... use of an artificial neural network architecture for
recognizing handwritten digit data. The feed-forward
neural network, which was implemented in Java, was
designed to be modular and parameterized ... approximation capability. In
theory, a multi-layer feed-forward neural network with
enough nodes and hidden layers can approximate any
bounded function and its derivative to...
neural network models for formation and control
... 3
$\vee$
$\dot{\cdot}$
In
this
network,
nonlinear
transformation
was
made
only
of
cascade
of
linear
weighted
summation
and
sigmoid
nonlinearity.
That
is,
we
did
not
use
any
a
priori
knowledge
about
the
dynamical
structure
of
the
controlled
object.
The
learning
went
well
and
the
network
has
some
extent
of
generalization
capability.
In
the
learning,
we
still
used
the
feedback
torque
comma...
Tài liệu A COMPREHENSIVE QUANTITATIVE MODEL FOR ANALYZING BOND REFUNDING DECISIONS pptx
... replaced by a floating-rate bond, a floating-rate bond replaced by a fixed-rate bond,
and a floating-rate bond replaced by another floating-rate bond with a different index or a different margin.
MOTIVATION ... significantly better than a stopping-time model based on present value analysis.
One aspect of bond refunding analysis that has not been adequately treated to date is t...
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