Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications
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Hysteresis cellular neural networks for solving combinatorial optimization problems
- Trang 539-546
Hysteresis cellular neural networks are one of artificial neural networks which
work effectively against large scale problems. In the previous work, remarkable
methods have never been developed to overcome the defects of hysteresis cellular
neural networks. We then propose a novel architecture for combinatorial
optimization problems to overcome them. Experimental results indicate the
efficiency of...
#Hysteresis #Cellular neural networks #Artificial neural networks #Large-scale systems #Limit-cycles #Piecewise linear techniques #Electronic mail #Cellular networks #Computer architecture #Heuristic algorithms
Configurable multi-layer CNN-UM emulator on FPGA
- Trang 164-171
A new emulated digital multi-layer CNN-UM chip architecture called Falcon has
been developed. In this paper the main steps of the FPGA implementation are
introduced. Main results are as follows: CNN-UM architecture emulated on Xilinx
Virtex series FPGA, 3D non-linear spatio-temporal dynamics can be implemented on
this architecture. The critical parameters of the implementation in single layer
conf...
#Field programmable gate arrays #Cellular neural networks #Equations #Computer architecture #Very large scale integration #Signal processing #Analog computers #State feedback #Laboratories #Turing machines
Basic mammalian retinal effects on the prototype complex cell CNN universal machine
- Trang 251-8
The unique possibility for reconstructing the first stage of the visual system
on a programmable silicon chip is described. The developed mammalian retinal
model can be implemented as an analogic algorithm running on a prototype complex
cell cellular neural network processor. It enables the neuro-biological and
vision research communities to study the wisdom of biological visual
transformations de...
#Retina #Prototypes #Cellular neural networks #Turing machines #Visual system #Silicon #Biological system modeling #Design engineering #Biology computing #Neuroscience
New spatial-temporal patterns and the first programmable on-chip bifurcation test-bed
- Trang 25-32
In this paper we introduce a new experimental tool, a real-time programmable,
spatial-temporal bifurcation test-bed. We present the experimental analysis of
an antisymmetric template class. This class produces novel spatial-temporal
patterns that have complex dynamics. The character of these propagating patterns
depends on the self-feedback and on the sign of the coupling below the
self-feedback t...
#Bifurcation #Testing #Cellular neural networks #Chaos #Computer architecture #Equations #Educational institutions #Numerical simulation #Circuits #Nonlinear dynamical systems
A CNN path planning for a mobile robot in an environment with obstacles
- Trang 188-194
In this paper a method for visual control based on images of a mobile robot in
an environment with obstacles is proposed. Cellular neural networks are used
here for path planning of a mobile robot, in real time.
#Cellular neural networks #Path planning #Mobile robots #Navigation #Trajectory #Robot control #Pixel #Process planning #Signal processing #Image processing
CNN based central pattern generators with sensory feedback
- Trang 275-282
In this paper the topic of including feedback from sensors in the central
pattern generator (CPG) for a hexapod robot realized through cellular neural
networks (CNNs) is addressed. An approach based on local bifurcation of the CNN
cells constituting the sub-units of the CPG network is introduced, allowing
control of the direction of the robot. Suitable control can be realized by
changing the value...
#Cellular neural networks #Feedback #Neurofeedback #Legged locomotion #Orbital robotics #Neurons #Animal structures #Robot sensing systems #Control systems #Couplings
A study on limit cycles in nearly symmetric cellular neural networks
- Trang 41-46
It is known that symmetric cellular neural networks (CNNs) are completely
stable, i.e., each trajectory converges towards some equilibrium point. The
paper addresses the issue of the loss of CNN complete stability caused by errors
in the implementation of the nominal symmetric interconnections. The main result
is a structural condition which implies the existence of stable limit cycles
generated v...
#Limit-cycles #Intelligent networks #Cellular neural networks #Neurons #Symmetric matrices #Bifurcation #Neural networks #Differential equations #Robust stability #Stationary state
Analogue weighted median filter based on cellular neural network for standard video signal processing
- Trang 638-645
A VLSI implementation of an analogue weighted median filter based on Cellular
Neural Network (CNN) paradigm for standard video signal processing is described
in this paper. This filter consists of feedforward nonlinear template B
operating within the window of 3 by 3 pixels around the central pixel being
filtered. The feedforward nonlinear coefficients are realized using a
programmable nonlinear c...
#Cellular neural networks #Signal processing #Digital filters #Circuits #Information filtering #Information filters #Nonlinear filters #Brightness #Pixel #Differential equations
Object-oriented image analysis via analogic CNN algorithms. II. Image synthesis and consistency observation
- Trang 180-187
For pt.I see ibid., p.172-9 (2002). In the context of image analysis for
object-oriented coding schemes, this paper presents new analogic CNN algorithms
for implementing the image synthesis and consistency observation stages. Along
with the motion estimation algorithm illustrated in the companion paper, the
proposed approach represents a framework for implementing CNN-based real-time
image analysi...
#Image analysis #Cellular neural networks #Image generation #Image motion analysis #Image color analysis #Image segmentation #Image sequence analysis #Motion estimation #Image coding #Object oriented modeling
mL-CNN: a CNN model for reaction-diffusion processes in m-component systems
- Trang 98-106
A mL-CNN is presented in this paper as a generalization of CNN models of
reaction-diffusion processes in nonlinear media with m components. Main
properties of the model are considered in accordance with imaginations of the
process "mechanisms". Two particular CNN models, an autonomous 2L-CNN and a
2L-CNN with external inputs, are presented as examples of special cases of the
mL-CNN. Emergence of s...
#Cellular neural networks #Neurons #Geophysics computing #Mathematics #Mathematical model #Electronic circuits #Circuit simulation #Piecewise linear techniques