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
CMOS realization of a 2-layer CNN universal machine chip
- Trang 444-51
Some of the features of the biological retina can be modelled by a cellular
neural network (CNN) composed of two dynamically coupled layers of locally
connected elementary nonlinear processors. In order to explore the possibilities
of these complex spatio-temporal dynamics in image processing, a prototype chip
has been developed by implementing this CNN model with analog signal processing
blocks. ...
#Cellular neural networks #Turing machines #Biological system modeling #Semiconductor device modeling #CMOS technology #Retina #Couplings #Nonlinear dynamical systems #Image processing #Prototypes
Nonlinear dynamics and propagation in positive feedback comparators for A/D Converters
- Trang 415-421
In this paper a link is made between dynamics and propagation in a chain of
resistively coupled cells and the behavior of positive feedback comparators
which are the primary blocks in analog to digital converters (ADC). It is
pointed out that both behaviors can be explained with the same nonlinear
dynamics. It turns out that an important property of the common unique cell is a
two stable equilibri...
#Feedback #Cellular neural networks #Circuits #Nonlinear equations #Resistors #Nonlinear dynamical systems #Microelectronics #Laboratories #Neurophysiology #Cardiology
Influence of system non-uniformity on dynamic phenomena in arrays of coupled nonlinear networks
- Trang 115-123
In this paper we investigate the influence of system non-uniformity on the
existence and stability of synchronous motion in an array of bi-directionally
coupled electronic circuits. In computer simulations we find the level of
nonuniformity for which synchronous behavior is sustained. We also present
several examples of attractors, which appear when the synchronous motions is no
longer stable.
#Nonlinear dynamical systems #Intelligent networks #Coupling circuits #Chaos #Circuit stability #Bidirectional control #Cellular neural networks #Oscillators #Piecewise linear techniques #Capacitors
Delay-driven contrast enhancement using a cellular neural network with state-dependent delay
- Trang 202-208
We design a cellular neural network model with state-dependent delay to perform
delay-driven contrast enhancement on continuous image sequences, e.g., in moving
image data. We report here some preliminary results of a simulation of this
system using a recently-released algorithm for solving systems of delay
differential equations containing state-dependent delays.
#Cellular neural networks #Delay #Personal digital assistants #Pervasive computing #Object detection #Integrated circuit modeling #Equations #Mathematics #Neural networks #Impedance
Visual feedback by using a CNN chip prototype system
- Trang 291-298
Robot locomotion control passes through a series of sensors that, according to
information from the environment, allow the robot to adapt, in real time, its
locomotion scheme or trajectory. When the goal of the robot is to reach a target
in a non-structured environment the best approach is visual control realized by
a fast image processing system. Fast parallel image processing of the CNN-UM
cP400...
#Feedback #Cellular neural networks #Prototypes #Robot kinematics #Cameras #Control systems #Working environment noise #Pixel #Image processing #Filtering
Fingerprint image enhancement using CNN Gabor-Type filters
- Trang 377-382
Fingerprint images are usually worsened by various kinds of noise causing
cracks, scratches and bridges in the ridges as well as ink blurs. These cause
matching errors in fingerprint recognition. For effective recognition the
correct ridge pattern is essential, requiring the enhancement of fingerprint
images. A fingerprint pattern consists of ridges. Segment by segment analysis of
the pattern yiel...
#Fingerprint recognition #Image matching #Cellular neural networks #Gabor filters #Image segmentation #Matched filters #Bridges #Ink #Pattern recognition #Image recognition
Characterizing the spatio-temporal dynamics of the epileptogenic process with nonlinear EEG analyses
- Trang 228-242
In this overview we present our work investigating the spatio-temporal dynamics
of the epileptogenic process using time series analysis techniques derived from
the theory of nonlinear dynamics. Apart from a localization of epileptic foci in
different anatomical locations during the seizure-free interval we discuss
possibilities for seizure prediction, a field that represents one of the
greatest ch...
#Epilepsy #Electroencephalography #Electrodes #Time series analysis #Humans #Drugs #Surgery #Medical treatment #Physics computing #Nuclear physics
On the relationship between CNNs and PDEs
- Trang 16-24
The relationship between cellular neural/nonlinear networks (CNNs) and partial
differential equations (PDEs) is investigated. The equivalence between a
discrete-space CNN model and a continuous-space PDE model is rigorously defined.
The problem of the equivalence is split into two sub-problems: approximation and
topological equivalence, that can be explicitly studied for any CNN models. It
is know...
#Cellular neural networks #Mathematical model #Partial differential equations #Differential equations #Cellular networks #Biological system modeling #Circuit simulation #Fluid dynamics #Bifurcation #Automation
Moving object tracking on panoramic images
- Trang 63-70
Analogic CNN algorithms are combined with the special properties of a panoramic
imaging device called PAL optics. The resulting system is capable to identify
and track moving objects in 360 degrees field of view real-time. Image
processing engine was the ALADDIN system with a 64/spl times/64 array size CNNUM
chip. As the image sensor, we tested the optical input of the CNNUM chip in one
experiment...
#Optical devices #Optical sensors #Cellular neural networks #Optical imaging #Real time systems #Image processing #Engines #Image sensors #Testing #Cameras