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Midwest Symposium on Circuits and systems (MWSCAS)

作者： D. Gantla H.S. Abdel-Aty-Zohdy R.L. Ewing Microelectronics System Design Laboratory Department of Electrical & Systems Engineering Oakland University Rochester MI USA Wright Patterson Air Force Base OH USA

In an olfaction system (E-Nose) hardware implementation, outputs from the GA approach are used as inputs to an intelligent neural network system for biochemical detection and decision-making. In this paper we present a Genetic Algorithm for measurement characterization with dynamic inputs. Input measurements are from a given range and are assumed in parallel from chemical-sensor array. An input multiplexer/controller/Analog-Digital converter preprocessing stage is used to control these input measurements. The new dynamical approach presents measurement characterization and also optimum fused measurements without loosing the integrity of incoming signals. Through a novel mutation and crossover approach (Half Sibling and A Clone) optimum characteristic weight chromosomes are achieved. HSAC represents both crossover and mutation. A key feature of the new approach is that no pre-assigned minimum error is specified, rather error is dynamically evaluated based on measurements. Simulation results of the new GA with dynamic measurements are compared with one of the approaches from GAlib (A library of genetic Algorithm approaches from MIT) and proved the new approach has minimum error and a early convergence. MATLAB has been used as the simulation tool.

关键词： Genetic algorithms Biosensors Genetic mutations Neural network hardware Intelligent systems Intelligent networks Intelligent sensors Neural networks Decision making Chemicals

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Modeling and simulation for on-chip power grid networks by locally dominant krylov subspace method

Modeling and simulation for on-chip power grid networks by l...

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2008 International Conference on Computer-Aided design, ICCAD

作者： Yan, Boyuan Tan, Sheldon X.-D. Chen, Gengsheng Wu, Lifeng Department of Electrical Engineering University of California Riverside CA 92521 United States ASIC and System State-Key-Lab Microelectronics Dept. Fudan Univeristy Shanghai 200433 China Cadence Design Systems Inc. San Jose CA 95134 United States

ISBN: (纸本)9781424428205

Fast analysis of power grid networks has been a challenging problem for many years. The huge size renders circuit simulation inefficient and the large number of inputs further limits the application of existing Krylov-subspace macromodeling algorithms. However, strong locality has been observed that two nodes geometrically far have very small electrical impact on each other because of the exponential attenuation. However, no systematic approaches have been proposed to exploit such locality. In this paper, we propose a novel modeling and simulation scheme, which can automatically identify the dominant inputs for a given observed node in a power grid network. This enables us to build extremely compact models by projecting the system onto the locally dominant Krylov subspace corresponding to those dominant inputs only. The resulting simulation can be very fast with the compact models if we only need to view the responses of a few nodes under many different inputs. Experimental results show that the proposed method can have at least 100X speedup over SPICE-like simulations on a number of large power grid networks up to 1M nodes.

关键词： Circuit simulation

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Optimal-weights sensors-measurement fusion using genetic algorithms

Optimal-weights sensors-measurement fusion using genetic alg...

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Midwest Symposium on Circuits and systems (MWSCAS)

作者： M.S. Sharawi H.S. Abdel-Aty-Zohdy R.L. Ewing Microelectronics System Design Laboratory Electrical and Systems Engineering Oakland University Rochester MI USA US Air Force Research Laboratory Dayton OH USA

ISBN: (纸本)078037150X

Although there are many simulated Genetic Algorithms (GAs) in applications, less research has been directed toward their practical hardware implementations. In this paper we present a GA for optimum sensors-measurement fusion and characteristic weights. A multilevel verification of the GA is performed via the Mentor Graphics design Architect (DA) and ModelSim CAD tools. In particular the design of efficient universal multipliers, dividers, and their integrated circuits is addressed. Effective mutation and crossover approach has been implemented in the GA system operation. It requires 960 clock cycles for complete iteration of 64 chromosomes, each with 3 genes of two binary-bits. This requires only 12 /spl mu/sec when implemented in the 0.25 /spl mu/m CMOS technology. The GA system is developed for a preprocessing unit to select optimal weights from real-time sensors measurement, and for fused measurements as in an electronic nose, integrated accelerometer systems, and for performance enhancement of recurrent dynamic neural networks in noisy environments. The proposed approach, simulation results, and possible experimental results are presented.

关键词： Genetic algorithms CMOS technology Hardware Graphics design automation Genetic mutations Clocks Biological cells Integrated circuit technology Real time systems

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Research on workflow recognition for liver rupture repair surgery

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Mathematical Biosciences and engineering 2024年第2期21卷 1844-1856页

作者： Men, Yutao Zhao, Zixian Chen, Wei Wu, Hang Zhang, Guang Luo, Feng Yu, Ming Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China Medical Support Technology Research Department Systems Engineering Institute Academy of Military Sciences People’s Liberation Army Tianjin300161 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

Liver rupture repair surgery serves as one tool to treat liver rupture, especially beneficial for cases of mild liver rupture hemorrhage. Liver rupture can catalyze critical conditions such as hemorrhage and shock. Surgical workflow recognition in liver rupture repair surgery videos presents a significant task aimed at reducing surgical mistakes and enhancing the quality of surgeries conducted by surgeons. A liver rupture repair simulation surgical dataset is proposed in this paper which consists of 45 videos collaboratively completed by nine surgeons. Furthermore, an end-to-end SA-RLNet, a self attention-based recurrent convolutional neural network, is introduced in this paper. The self-attention mechanism is used to automatically identify the importance of input features in various instances and associate the relationships between input features. The accuracy of the surgical phase classification of the SA-RLNet approach is 90.6%. The present study demonstrates that the SA-RLNet approach shows strong generalization capabilities on the dataset. SA-RLNet has proved to be advantageous in capturing subtle variations between surgical phases. The application of surgical workflow recognition has promising feasibility in liver rupture repair surgery. ©2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons.

关键词： Image classification

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Plasticity recurrent spiking neural networks for olfactory pattern recognition

Plasticity recurrent spiking neural networks for olfactory p...

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Midwest Symposium on Circuits and systems (MWSCAS)

作者： J.N. Allen H.S. Abdel-Aty-Zohdy R.L. Ewing Microelectronics System Design Laboratory Department of Electrical and System Engineering Oakland University Rochester MI USA Information Directorate Air Force Research Laboratory OH USA

This paper introduces a novel spiking neural network methodology, and applies it to an odorant learning and detection application. Spike-time dependent plasticity can support coding schemes that are based on spatio-temporal spike patterns. Spiking (or pulsed) neural networks (SNNs) are models which explicitly take into account the timing of inputs. The network input and output are usually represented as series of spikes (delta function or more complex shapes). Plasticity SNNs have an advantage of being able to recurrently process information. Spike-time dependent plasticity can enhance signal transmission by selectively strengthening synaptic connections that transmit precisely timed spikes at the expense of those synapses that transmit poorly timed spikes. Complete theory describes the spiking network's digital implementation. Theory is verified using simulation of a biologically plausible odor environment with 1023 odor receptor inputs. Stochastic on-chip learning uses sampling and a correlation filter to learn odors despite noisy environment conditions. Simulation and Verilog chip design are tested on a field programmable gate array. A scalable field programmable gate array implementation with 1024 inputs, 1 output, and expansion capability for unlimited outputs is synthesized into 87,062 gates

关键词： Neural networks Recurrent neural networks Olfactory Pattern recognition Biological system modeling Field programmable gate arrays Timing Shape Stochastic processes Sampling methods

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Exploring the biocomputing frontier

Exploring the biocomputing frontier

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Midwest Symposium on Circuits and systems (MWSCAS)

作者： R.L. Ewing H.S. Abdel-Aty-Zohdy F. Schuermeyer L. Liou J.B. Moncrief M. Rubeiz M. Williamson Air Force Research Laboratory OH USA Microelectronics System Design Laboratory Department of Electrical and System Engineering Oakland University Rochester MI USA Department of Electrical Engineering Wright State University Dayton OH USA

Stop thinking that the universe is best described by Boolean order operations, consider the world of biocomputing. The idea in exploring the multidimensional characteristics of biocomputing systems involves multilevel protein logic interaction with hybrid digital systems (bio/digital/analog systems). In the protein biocomputing world, all models are multilevel and nonlinear exponential in nature. These biocomputing systems are linearized by boundary limited frequency, time response and dimensional ranges. The protein model and its correct development is probably the most difficult aspect for biocomputing issues. Previous protein models were not dealing with 2 and 3 dimensional models, while the current protein models are now faced with high frequency design, due to the emergence of bio-nanodevices. These future biocomputing devices will be chemical sensors, fluidic computer systems, optical switches, nanoactuators, self-repairing polymorphic computing systems, cognitive processors and biorobotics

关键词： Frequency Optical computing Multidimensional systems Logic Digital systems Time factors Protein engineering Chemical sensors Optical switches Nanoscale devices

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design approach for biomedical smart sensors

Design approach for biomedical smart sensors

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Midwest Symposium on Circuits and systems (MWSCAS)

作者： R.L. Ewing H.S. Abdel-Aty-Zohdy Air Force Research Laboratory Inforamation Directorate Adjunct Professor Department of Electrical and Computer Engineering Air Force Institute of Technology USA Microelectronics System Design Laboratory Department of Electrical and Systems Engineering Oakland University Rochester MI USA

ISBN: (纸本)078037150X

system-on-Chip solid state circuits that sense, receive, transmit, and process signals are the sensors, or eyes and ears, of the medical field of the millennium. The goal and design of the system-on-Chip (SOC) program for industry will be to provide affordable, reproducible, and reliable front-end instrumentation, components and subsystems for medical systems. To process/store/analyze the signals acquired from these medical sensors, analog/digital systems are used to provide data fusion and information extraction. These biomedical smart sensors cover the hybrid domains of mixed-technology (electrical, mechanical, optical, thermal, biochemical) and mixed-concept (electrical, control, digital signal processing). These significant domain design differences impose robust design challenges for medical sensor technology.

关键词： Intelligent sensors Biosensors system-on-a-chip Signal processing Sensor systems Mechanical sensors Solid state circuits Eyes Ear Instruments

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Efficient test generation for built-in self-test boundary-scan template

Efficient test generation for built-in self-test boundary-sc...

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1991 IEEE VLSI Test Symposium: Chip-to-system Test Concerns for the 90''s, VTEST 1991

作者： Nagvajara, P. Karpovsky, M.G. Levitin, L.B. Dept. of Electr. and Comput. Eng. Drexel Univ. PhiladelphiaPA United States Research Laboratory for Design and Testing of Computer and Communication Systems Department of Electrical Computer and System Engineering Boston University United States

An analysis and design of a pseudorandom pattern generator, (PRPG), based on a linear recurrence, for built-in self-test (BIST) boundary scan design is presented. The authors present for the case when r≥s, a design of an s-stage PRPG capable of producing 2s-1 distinct r-bit patterns within 2s-1 clock pulses independent of the hardware realization of the PRPG. For the case when rr distinct r-bit patterns and the expected number T(N) of distinct patterns given a number N of clock pulses were presented. The proposed theoretical average N(T) was shown to be close to the experimental average values Nex(T). Hence, the value N(T) or T(N) can be used as a benchmark for evaluating the efficiency of a BIST boundary scan test generation. © 1991 IEEE.

关键词： Built-in self test

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Wavelet-multifractal processing of signals

Wavelet-multifractal processing of signals

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IEEE Asia-Pacific Conference on Circuits and systems

作者： K. Soemintapura A.Z.R. Langi Laboratory for Signals and Systems Department of Electrical Engineering Institute of Technology Bandung Laboratory of Microelectronics Design IURC Microelectronics Institute of Technology Bandung Bandung West Java Indonesia

This research develops a new approach in processing multimedia signals (i.e., speech, audio, and images) using wavelets and multifractals. Processing multimedia signals is critical in many modern telecommunication and information systems. Nonstationary behaviours have been the most important characteristics of multimedia signals because they carry signal information. Unfortunately nonstationary parts are difficult to process effectively using traditional tools such as Fourier transforms. In contrast, wavelets and multifractality not only reveal that nonstationary parts are sufficient to represent natural images, but also can be used to reconstruct such signals. The general objectives of this research are to develop the wavelet and multifractal concepts into a new signal-processing framework, to obtain more effective and efficient signal representation. If the objectives can be achieved, the results of the proposed research can be a breakthrough in nonstationary signal processing, as fundamental as the well known Fourier approach in stationary signal processing.

关键词： Signal processing Feature extraction Fractals Signal analysis Laboratories microelectronics Signal synthesis Character recognition Data mining Signal design

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Polymorphic Architecture for an Electronic Nose (eNose)

Polymorphic Architecture for an Electronic Nose (eNose)

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Midwest Symposium on Circuits and systems (MWSCAS)

作者： R.L. Ewing H.S. Abdel-Aty-Zohdy J.R. Morrison Information Directorate U.S. Air Force Research Laboratory OH USA Microelectronics System Design Laboratory Department of Electrical and Systems Engineering Oakland University Rochester MI USA

Bioinspired evolvable techniques significantly increase the functionality of autonomous low-power detection systems by enabling them to learn, adapt and self-reconfigure through use of programmable BioFET devices. Electronic artificial noses or sniffers as bioinspired devices are under development that produces holograms stored within three-dimensional protein memory structures enabling automated real-time detection and classification of odors, vapors and contamination within gases.

关键词： Electronic noses Laboratories Protein engineering Chemical technology Sensor arrays Neural networks Leak detection Gases Computerized monitoring FETs

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