Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications
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Delay-driven contrast enhancement using a cellular neural network with state-dependent delay
Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications - - 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
Characterizing the spatio-temporal dynamics of the epileptogenic process with nonlinear EEG analyses
Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications - - 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
Application issues of a programmable optical CNN implementation
Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications - - Trang 156-163
A programmable opto-electronic analogic CNN computer (POAC) provides an
efficient frame for diverse image processing applications, as it combines the
enormous inherent computational capabilities of our new, massively parallel, but
flexibly programmable optical CNN implementation with the capabilities of a
visual CNN-UM chip. Our optical CNN implementation is based on an original,
semi-incoherent o...
#Cellular neural networks #Application software #Concurrent computing #Optical computing #Correlators #Real time systems #Image processing #Computer architecture #Fourier transforms #Microelectronics
Fingerprint image enhancement using CNN Gabor-Type filters
Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications - - 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
Boolean design of binary initialized and coupled CNN image processing operators
Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications - - Trang 124-131
As soon as an image processing operator can be expressed as a linearly separable
Boolean function involving a cell and its neighborhood, there is a way of
straightforwardly deriving an equivalent cellular neural network (CNN)
operation. An appropriate method had already been introduced for the robust
design of uniformly initialized uncoupled CNN operators, and is now applied to
the design of binar...
#Cellular neural networks #Image processing #Convolution #Robustness #Nonlinear filters #Boolean functions #Output feedback #State feedback #Image analysis #Design methodology
On the dynamics of a class of cellular neural networks
Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications - - Trang 92-97
The stability and dynamics of a class of cellular neural networks (CNN) in the
central linear part is investigated using the decoupling technique based on
discrete spatial transforms, Nyquist and root locus techniques.
#Cellular neural networks #Eigenvalues and eigenfunctions #Piecewise linear techniques #Equations #Telecommunications #Stability #Discrete transforms #Image processing #Circuits #Radio control
Configurable multi-layer CNN-UM emulator on FPGA
Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications - - 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
Improvement of the method for uncoupled binary input-output CNN template decomposition
Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications - - Trang 459-466
This paper proposes an improved method for systematic decomposition of Boolean
operators into a sequence of simpler ones. The improvement has two main
components: (i) a sufficient condition for decreasing the number of possible
child-templates during decomposition; (ii) pointing out the template element,
the elimination of which results in the possibly maximum increment of the
robustness value of ...
#Cellular neural networks #Robustness #Fault tolerance #Software libraries #Design methodology #Testing #Logic functions #Laboratories #Sufficient conditions #Cellular networks
Nonlinear dynamics and propagation in positive feedback comparators for A/D Converters
Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications - - 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
Hardware-oriented algorithm for associative memories on cellular neural networks
Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications - - Trang 532-538
We present a new learning algorithm used to implement associative memories on
digital cellular neural networks. The algorithm can be easily implemented in
hardware or simulated on a digital computer without numerical errors. These
attractive features come from the finite precision of connection weights,
automatically taken into account as a design constraint; moreover, no
multiplication is needed ...
#Cellular neural networks #Hardware #Associative memory #Computational modeling #Computer architecture #Error correction #Memory architecture #Cellular networks #Distributed computing #Computer networks
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