Ioana Dogaru

Chaotic Scan: A Low Complexity Video Transmission System for Efficiently Sending Relevant Image Features

A novel image scanning and transmission system is proposed, where the traditional raster scan is replaced with a new one, called a chaotic scan. The result is a low complexity image transmission system with encryption and spread spectrum capabilities well suited for compressed sensing applications. Due to the uncorrelated nature of the consecutively scanned pixels, it allows a form of progressive compression and fast discovery of the relevant image features using only a small fraction of the transmitted pixels. The key ingredient of the proposed system is a chaotic counter addressing the sensor array, based on a cellular automaton exhibiting a pseudo-random chaotic behavior and binary synchronization property.

An efficient finite precision RBF-M neural network architecture using support vectors

This paper investigates the effects of using limited precision for efficient implementations of the RBF-M neural network. This architecture employs only simple arithmetic operators and is characterized by simple LMS training in an expanded feature space generated by RBF functions centered around support vectors selected via a simple algorithm. The classification performances of our low complexity, finite precision architecture are similar and even better to those obtained using the more complex SVM.

Algebraic normal form for rapid prototyping of elementary hybrid cellular automata in FPGA

This paper introduces a methodology based on algebraic normal form representations and software tools to rapidly generate the VHDL code description of elementary hybrid cellular automata with arbitrary parameters. Such parameters include the CA local rule, the number of cells and the mask, which is specific for hybrid CA. This tool allows rapid synthesis of various CA types, as they are required by various applications. Synthesis, post-place and route and functional simulation are given for a specific case of a random number generator to prove the functionality of our software tools.

A smart sensor architecture based on emergent computation in an array of outer-totalistic cells

A novel smart-sensor architecture is proposed, capable to segment and recognize characters in a monochrome image. It is capable to provide a list of ASCII codes representing the recognized characters from the monochrome visual field. It can operate as a blinds aid or for industrial applications. A bio-inspired cellular model with simple linear neurons was found the best to perform the nontrivial task of cropping isolated compact objects such as handwritten digits or characters. By attaching a simple outer-totalistic cell to each pixel sensor, emergent computation in the resulting cellular automata lattice provides a straightforward and compact solution to the otherwise computationally intensive problem of character segmentation. A simple and robust recognition algorithm is built in a compact sequential controller accessing the array of cells so that the integrated device can provide directly a list of codes of the recognized characters. Preliminary simulation tests indicate good performance and robustness to various distortions of the visual field.

FPGA implementation of chaotic cellular automaton with binary synchronization property

In this paper a FPGA implementation of a cellular automaton defined by rule 101 and it s negate is presented. Such HCA (hybrid cellular automata) was previously proved to behave as a pseudo noise sequence generator with the additional binary synchronization property and with demonstrated capabilities in reducing the overall complexity of image transmission systems. The raster scan is replaced by a chaotic scan provided by HCA. That allows implementation a progressive image compression and spread spectrum transmission with the advantage in low complexity implementation. A VHDL description of the HCA counter is provided for an arbitrary number of cells n. The resulting hardware complexity is several tens of times lower than needed for implementation of other pseudo noise generators reported in the literature.

Efficient realizations of a sound propagation processor as a cellular nonlinear network

This paper investigate several aspects for efficiently implementing a sound propagation processor as a nonlinear cellular network. Starting from a partial differential wave propagation equation an equivalent cellular array is defined to simulate a certain 2-dimensional scenario space where various obstacles and signal sources may be positioned arbitrarily. The defining equations in the initial model with 5 state variables per cell are redefined into a much faster model with 2 state variables per cell. Consequently two cell processors (the state and the output processors) are defined from the perspective of implementing arrays of such interconnected processors in FPGA technology. Finite precision effects were investigated concluding that at least 10 bits precision is necessary in order to have acceptable simulation errors.

Binary synchronization in cellular automata for building compact CDMA systems

A novel spread spectrum communication system is proposed, being characterized by a very compact yet efficient implementation. A particular elementary cellular automaton with rule 45 is used as the generator of spreading sequences while it also has synchronization capabilities. Simulations demonstrate that generated sequences are orthogonal and the performances of the proposed system are comparable to those of more sophisticated CDMA systems.

A Low Cost High Performance Computing Platform for Cellular Nonlinear Networks Using Python for CUDA

A novel platform (hardware and software) for complex systems modeling is proposed. It exploits the newest developments in both software (Continuums - Anacondas Numba and Numbapro Python packages) and hardware (the use of parallel computation on GPU provided by the CUDA computing platform) to ensure high-performance, high-productivity and high-portability in developing and simulating models of cellular nonlinear networks (CNN). A particular example is given in this paper for the case of Reaction Diffusion CNN and its effectiveness it is analyzed. It is shown that the hardware resources are effectively exploited while using a programming style closer to scientific computing and with a short learning cycle. With our low cost implementation we were able to achieve very good performance in implementing a Reaction-Diffusion CNN (about 500 Mcells/second). The platform can be easily extended to support a broader spectrum of computational models similar to CNNs, such as the Finite Difference Time Domain models for various physical processes.

An efficient sound propagation software simulator based on cellular automata

A software simulator based on cellular nonlinear networks used to model the sound wave propagation equation is proposed and its performances are evaluated. For applications in robotics the simulator is conceived as a kernel upon which one may build up additional software modules to generate various navigation scenarios. Consequently our simulator allows to do various virtual experiments, useful for the design of various parts from a bio-inspired sensor system Such experiments include the study of sensor geometry, the influence of the transmitting ultrasonic signal sensor and many others.

Binary synchronization of chaos in hybrid cellular automata for low complexity image compression and transmission

This paper exploits an interesting property of a certain type of elementary cellular automata, namely hybrid cellular automata (HCA) defined by rule 101 and its negate. Such HCA may be easily implemented on any CNN platform, and has some interesting properties. It provides a chaotic counting automaton instead of the traditional raster scan counter addressing the multiple sensing elements. Replacing raster scan with chaotic scan provided by the HCA allows implementation of both progressive image compression and spread spectrum transmission with a very low complexity of the transmitting sensor. The clear advantages of our system in terms of implementation complexity, makes it a valuable candidate for low power sensor networks applications.