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Energy diffusion model of bR for voxel identification

Energy diffusion model of bR for voxel identification

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Midwest Symposium on Circuits and systems (MWSCAS)

作者： D. Garcia Neto H.S. Abdel-Aty-Zohdy Microelectronics System Design Laboratory-Department of Electrical and Systems Engineering Oakland University Rochester USA

In this paper, a potential biological structure for computer volumetric memory is investigated. Bacteriorhodopsin is a protein found in the purple membrane of the bacteria Halobacterium salinarum. This protein has light absorption properties that generate different stable states allowing the use of multilevel logic as well as binary logic. CHARMmtrade has been used to simulate the energy response of Bacteriorhodopsin at room temperature 300K for the bR ground state and the other states. The K state takes place after blue light (lambda= 635nm) absorption on the bR state. The energy difference is found to be an increase of 1086.92 kcal/mol which is responsible for triggering the photocycle that also includes the states K, L, M, N, and O. An energy surplus is found between O and bR state that may be spread to surrounding molecules. However, conformational interference does not produce photons necessary for the isomerization reaction. Further quantum molecular (QM) analysis should provide an extended model for this macromolecular energy study

关键词： Biological system modeling Proteins Absorption Logic Biology computing Biomembranes Microorganisms Computational modeling Land surface temperature Stationary state

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A hardware implementation of genetic algorithms for measurement characterization

A hardware implementation of genetic algorithms for measurem...

引用

IEEE International Conference on Electronics, Circuits and systems (ICECS)

作者： M.S. Sharawi J. Quinlan H.S. Abdel-Aty-Zohdy Microelectronics System Design Laboratory Electrical and Systems Engineering Oakland University Rochester MI USA

To process/store/analyze signals acquired from sensors, hybrid systems with flexible and adaptable intelligent information processing and perception (IIPP) are needed. Genetic algorithms (GA) present a suitable pre-processing operation because of their good convergence to optimum solutions and characterization capabilities. Most GAs are built via software because of their ease of editing and customization. Less attention has been given to hardware implementation of such algorithms. We present a hardware design approach of a GA for optimum measurement representation/characterization to a following IIPP stage. A multilevel verification of the GA is performed via VHDL. In particular the design of efficient universal multipliers and dividers is addressed. A new time efficient approach for crossover based on preassigned least error value is proposed. The crossover scheme is called half siblings and a clone. Such a scheme needs 10 iterations to converge the system proposed for sensor measurement characterization. This takes 7680 clock cycles, which is only 96 /spl mu/sec when implemented in the 0.25 /spl mu/m CMOS technology.

关键词： Hardware Genetic algorithms Intelligent sensors Sensor phenomena and characterization Sensor systems CMOS technology Information analysis Signal analysis Signal processing Information processing

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Signal perception and processing with bio-inspired sub-micro-systems

Signal perception and processing with bio-inspired sub-micro...

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2002 45th Midwest Symposium on Circuits and systems

作者： Abdel-Aty-Zohdy, Hoda S. Ewing, Robert L. Microelectronics System Design Lab. Department of Electrical Engineering Oakland University Rochester MI 48309 United States Information Directorate Air Force Research Laboratory Wright-Patterson AFB OH 45433 United States

Bio-inspired systems utilizing neural networks and genetic algorithms are presented in this paper for applications in pattern discovery, identification, classification, and optimum choices for Signal Perception and Processing (SPP), Sample overview applications are presented for: (I) Integrated Intelligent E-Nose systems, and (II) Communication systems dealing with: (1) Connection admission control;(2) Network congestion;(3) Resource management;(4) Priorities and constrains of service control;and (5) Application-specific network adaptation. Bio-inspired systems include: i-Self-Organizing feature Map for discovery, ii- Recurrent Dynamic Neural Networks (NNs), with output neurons feedback and feed forward arrays for noisy signals, iii- Reinforcement NNs for applications with only key features, rather than a known model, iv- Spiking NNs that adjust their synapses subject to changes in the environment, and v- Genetic Algorithms for characterization and optimization. This paper summarizes alternative combinations and structures of novel bio-inspired, VLSIC embedded systems for detection and quantification of bio-chemical agents, and optimum performance of SPP.

关键词： Signal processing

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A topological optical parametric amplifier on a CMOS-chip

A topological optical parametric amplifier on a CMOS-chip

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2023 Optica Nonlinear Optics Topical Meeting, NLO 2023

作者： Sohn, Byoung-Uk Huang, Yue-Xin Choi, Ju Won Chen, George F.R. Ng, Doris K.T. Yang, Shengyuan A. Tan, Dawn T.H. Photonics Devices and System Group Singapore University of Technology and Design Singapore487372 Singapore Research Laboratory for Quantum Materials Singapore University of Technology and Design Singapore487372 Singapore Institute of Microelectronics A*STAR 2 Fusionopolis Way #08-02 Innovis Tower Singapore138634 Singapore

ISBN: (纸本)9781957171234

We demonstrate 12.8dB optical parametric gain using a topological photonic waveguide based on the Su-Schrieffer-Heeger model with a domain wall, implemented on ultra-silicon-rich nitride. The Kerr nonlinearity is observed to induce delocalization in the topological mode. Optica Nonlinear Optics Topical Meeting 2023 © Optica Publishing Group 2023 © 2023 The Author(s)

关键词： Optical parametric amplifiers

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Analog computational circuits for neural network implementations

Analog computational circuits for neural network implementat...

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IEEE International Conference on Electronics, Circuits and systems (ICECS)

作者： M. Al-Nsour H.S. Abdel-Aty-Zohdy Microelectronics System Design Laboratory Department of Electrical and Systems Engineering Oakland University Rochester MI USA

High performance NMOS analog circuits which perform voltage addition, average weighing, and signal scaling are presented. Utilization of these circuits in artificial neural network applications is briefly discussed. The circuits are characterized by a simple structure which offers compactness, low voltage supply, and wide input range. In addition, inputs and outputs are voltages which eliminate the need for current voltage conversion. Hence, reduced power consumption and higher performance is achieved. A two-input analog adder has been accomplished through MOSIS 2.0 /spl mu/m n-well CMOS technology at Orbit Semiconductors, and occupies an area of 135/spl times/145 /spl mu/m/sup 2/. Inputs are within /spl plusmn/3 V for 3.3 V supply. Power consumption is less than 0.5 mW and THD is less than -36 dB. Measurements and performance evaluation are presented.

关键词： Analog computers Computer networks Neural networks Artificial neural networks Energy consumption CMOS technology MOS devices Analog circuits Low voltage Adders

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Reinforcement learning neural network circuits for electronic nose

Reinforcement learning neural network circuits for electroni...

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： H.S. Abdel-Aty-Zohdy M. Al-Nsour Microelectronics System Design Laboratory Department of Electrical and Systems Engineering Oakland University Rochester MI USA

This paper approaches electronic nose design from two promising angles: reinforcement neural network (RNN) learning algorithms, and naturally compatible analog circuits. This approach is inspired by biological sensing and discrimination of a multitude of odors in a background environment. A VLSI system approach is presented for classification of chemical compounds, with knowledge of key features only. Based on utilizing microsensor arrays, reinforcement neural networks are used to affect nonparametric pattern recognition, classification, and distinction among multicomponent chemicals. A specialized RNN approach is chosen. Realization and implementation of analog RNN circuits is presented using 1.2 /spl mu/m CMOS n-well technology, at AMI, through the MOSIS facilities. Preliminary results are satisfactory and lend evidence to the effectiveness of the analog designed neural network building blocks for temporal and spatial NN pattern recognition.

关键词： Learning Neural networks Electronic noses Recurrent neural networks Pattern recognition CMOS technology Algorithm design and analysis Analog circuits Very large scale integration Chemical compounds

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Reinforcement neural learning with application to gas sensors

Reinforcement neural learning with application to gas sensor...

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Midwest Symposium on Circuits and systems (MWSCAS)

作者： H.S. Abdel-Aty-Zohdy Microelectronics System Design Laboratory Department of Electrical and Systems Engineering Oakland University Rochester MI USA

Neural net reinforcement learning algorithm and its application to gas (chemicals) classification and quantification are considered in this paper. The approach does not require memory and has simplified reward/punishment computations. The advantages and disadvantages of the reinforcement algorithm are contrasted against other competing neural algorithms. The reinforcement learning has been found practical, when each gas (chemical) is distinguished by several features and characteristics with possible overlap. The paper also gives an account of integrated circuit digital chip implementation for typical four gases with temperature, pressure, and flow quantity features. The number of required iterations has been found to depend on reward and penalty parameters, as well as the threshold governing the learning. It is believed that our implementation approach has potential uses in auto industry safety and emission control, as well in automated semiconductor manufacturing process.

关键词： Gas detectors Learning Chemicals Neural networks Digital integrated circuits Gases Temperature Industrial control Manufacturing industries Safety

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An improved ASIC design and implementation for color space conversion applications

An improved ASIC design and implementation for color space c...

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Midwest Symposium on Circuits and systems (MWSCAS)

作者： M. Nsour H.S. Abdel-Aty-Zohdy Microelectronics System Design Laboratory Department of Electrical and Systems Engineering Oakland University Rochester MI USA

The design and VLSI implementation of an ASIC chip, which performs real time conversion, the Red, Green, and Blue (RGB) color coordinates to CIE (Commission Internationale de l'Eclairage) standard L* (luminance), a* (redness-greenness), and b* (yellowness-blueness) color coordinates, is presented. High-speed operation of this ASIC is achieved by pipelining the input data, and performing parallel operations. The ASIC is implemented using CMOS, 2.0 /spl mu/m, n-well process. It occupies an area of 1.55/spl times/1.45 mm/sup 2/. The chip is intended to be used in colorimetry manufacturing inspection and robotics precision. Inputs are 3 bits each. a* and b* are 7 bits each, L* is 6 bits.

关键词： Application specific integrated circuits systems engineering and theory Inspection Application software Humans Extraterrestrial measurements Instruments Color microelectronics Laboratories

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Formal verification and performance evaluation of logic integrated systems based on hierarchical analysis

Formal verification and performance evaluation of logic inte...

引用

Midwest Symposium on Circuits and systems (MWSCAS)

作者： F.A. El-Licy H.S. Abdel-Aty-Zohdy Microelectronics System Design Laboratory Department of Electrical and Systems Engineering Oakland University Rochester MI USA

ISBN: (纸本)078037150X

Formal verification of very large scale integrated circuit (VLSIC) involves the formal correctness of the functionality of a given design, while circuit validation involves the reliability and efficiency of the design. A hierarchical approach for computation, of IC design efficiency is proposed and implemented using figures of merit. The work has been motivated to partially complete an IC formal verification tool. The implemented system is integrated into a formal verification environment to reflect the performance of the verified system. The system is capable of analyzing the power dissipation and figures of merit using equivalent R and C components. The hierarchical analysis and evaluation of figures of merit general factors obtained at different system levels represent performance evaluation of each gate. An illustrative example of a 6/spl times/6 carry look-ahead adder is given and worst case conditions have been determined. The system performance may thus be improved.

关键词： Formal verification CMOS logic circuits Binary trees Power dissipation Semiconductor device modeling Laboratories Performance analysis Switches Delay effects Logic design

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Biologically-Based Signal Processing Chips with Emphasis on Telecommunication Defect Tracking and Reliability Estimation

Biologically-Based Signal Processing Chips with Emphasis on ...

引用

IEEE Pacific Rim Conference on Communications, Computers and Signal Processing

作者： Hoda S Abdel-Aty-Zohdy Microelectronics System Design Laboratory Department of Electrical and Computer Engineering Oakland University Rochester MI USA

This paper provides observations and motivations to mimic biological information processing. Alternative bio-inspired systems definitions, basics, approaches, algorithms, and chip implementations will be illustrated to offer a base of choice for bio-based Intelligent Information Processing (IIP) systems. Hybrid biological and bio-based IIP are briefly presented. Two specific applications follow with embedded bio-based systems: Bio-chemical sensing and detection E-nose; and Track improvements In the reliability of the software used in telecommunication network deployments. The biologically-based processing discoveries gleaned from observing the spikes in the brain activity of monkeys, introduced the concept of plasticity in synapses used in our embedded Spiking Neural Network (SNN) system for the E-Nose The mathematical construct of a defect tracking classifier is nonlinear, and the event to be recognized involves a sequentially varying or non-stationary phenomenon for telecommunication defect tracking and reliability estimation. Thus, Adaptive Recurrent Dynamic Neural Network (ARDNN) system using wavelet function as the basis improved the failure event estimation of software defect tracking in telecommunications and reduced the error from 88% to L25-8%.

关键词： Biomedical signal processing Signal processing algorithms Information processing Telecommunication network reliability Biological neural networks Application software Embedded software Brain Nonlinear dynamical systems Neural networks

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