In this paper, we demonstrate that many image processing and pattern formation effects of
the simple Cellular Neural Network (CNN) can be understood by means of a common …

Cellular Nonlinear/neural Network (CNN) technology is both a revolutionary concept and an
experimentally proven new computing paradigm. Analogic cellular computers based on …

This brief presents a wireless, low-power embedded system that recognizes hand gestures
by decoding surface electromyography (EMG) signals. Ten hand gestures used on …

Conventional digital computation methods have run into a se rious speed bottleneck due to
their serial nature. To overcome this problem, a new computation model, called Neural …

We present a class of time-delay anisotropic diffusion models for image restoration. These
models lead to asymptotic states that are selected on the basis of a contrast parameter and …

In this paper, a CNN‐based spatio‐temporal approach is introduced for finding the
endocardial (inner) boundary of the left ventricle from a sequence of echocardiographic …

This paper describes the electronic implementation of a four-layer cellular neural network
architecture implementing two components of a functional model of neurons in the visual …

Optical flow estimation is a critical mechanism for autonomous mobile robots as it provides a
range of useful information. As real-time processing is mandatory in this case, an efficient …

At the fascinating frontiers of neurobiology, mathematics and psychophysics, this book
addresses the problem of human and computer vision on the basis of cognitive modeling …

In this paper the fundamentals of Cellular Neural Networks (CNNs) are introduced.
Subsequently it is shown that, due to their locally distributed way of exchanging signals …