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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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Cognitive processing using spiking neural networks

Cognitive processing using spiking neural networks

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IEEE National Conference on Aerospace and Electronics (NAECON)

作者： Jacob N. Allen Hoda S. Abdel-Aty-Zohdy Robert L. Ewing Microelectronics System Design Laboratory Department of Electrical and Computer Engineering Oakland University Rochester Hills MI USA Air Force Research Laboratory OH USA

ISBN: (纸本)9781424444946

Powerful parallel cognitive processors can be developed by studying biologically plausible models of cognitive systems in animals and extrapolating key principles to be adapted for implementation in digital computer architectures. The network described here uses basic statistical methods such as proportion sampling on a massively parallel scale to create a general purpose pattern classifier. From these principles, we can achieve auto association and self organization that provides fundamental cognitive processing. Signal preprocessing is essential to transform the signal into a scale and rotation invariant binary pattern. The network avoids the curse of dimensionality by filtering out irrelevant inputs, allowing us to combine large sensor input vectors from multiple sources. Recent hardware designs define the network structure and state in memory, and then use accelerator processor cores to modify these memory structures in parallel.

关键词： Neural networks Neurons Biological system modeling Biology computing Biological information theory Brain modeling Computer architecture microelectronics Power engineering and energy Biosensors

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Agile hardware development with rapid hardware definition language

Agile hardware development with rapid hardware definition la...

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IEEE International Conference on Electro-Information Technology

Rapid HDL is a hardware definition language developed in C# for the Microsoft .Net platform. Rapid HDL unifies digital FPGA hardware development and co-software integration. Hardware is scripted using reusable software objects, communication between hardware and software is automatic, and synthesis is automated using a free tool chain. Rapid HDL represents 18,000 lines of code and is freely available under the MIT license.

关键词： Hardware design languages Software libraries Testing Licenses microelectronics Force sensors Field programmable gate arrays Software reusability Software tools High level languages

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XML defined custom microprocessors using Rapid Hardware Definition Language

XML defined custom microprocessors using Rapid Hardware Defi...

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IEEE National Conference on Aerospace and Electronics (NAECON)

Rapid HDL is an object oriented software library for scripting the generation of synthesizable Verilog. A fully functional customized microprocessor is defined and automatically synthesized for an FPGA from an XML specification file. Using a library of blocks, a microprocessor fabric is defined in XML. Control states specify the connections between the fabric blocks during microprocessor operation. Opcodes sequence the control states and provide a vocabulary for assembly programs, which are compiled and executed on the microprocessor.

关键词： Microprocessors Hardware design languages Hardware XML Registers Fabrics Software

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Fractional-Order Signal Processing using a Polymer-Electrolyte Transistor

Fractional-Order Signal Processing using a Polymer-Electroly...

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51st Midwest Symposium on Circuits and systems (MWSCAS 2008), vol.2

作者： Robert L. Ewing Hoda S. Abdel-Aty-Zohdy Michael C. Hollenbeck Kenneth S. Stevens Information Directorate US Air Force Research Laboratory OH USA Microelectronics System Design Laboratory Department of Electrical and Systems Engineering Oakland University Rochester MI USA Department of Electrical and Computer Engineering University of Utah Salt Lake UT USA

Fractional-order systems have applications in the areas of Flight Control, Robotics, Missile Guidance, Control of Structural Vibrations of Space Platforms and Sensor Technology. Fractional-order transfer functions can characterize complex nonlinear dynamics with many fewer parameters than integer-order functions. This paper addresses the use of a polymer-electrolyte transistor (PET) for use in implementating fractional-order algorithms for signal processing. The PET's advantage over the conventional RC and RL circuits is that it can be both functionally scaled and varied for dynamic fractional-order parameter controllability.

关键词： Fractional-Order Signal Processing Polymer-electrolyte transistor Acid/base chemistry Diffusion Electrokinetic flow

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Domain distributed intelligent processing for information fuselets

Domain distributed intelligent processing for information fu...

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： R.L. Ewing H.S. Abdel-Aty-Zohdy US Air Force Research Laboratory Information Directorate Air Force Institute of Technology Dayton OH USA Dept of Electrical & Systems Engineering Microelectronics System Design Laboratory Oakland University Rochester MI USA

ISBN: (纸本)0780366859

The best solution for one intelligent information fusion design is obviously domain specific and not universal. This is especially true in multidisciplinary design domains of information systems at higher clock speeds where the need arises to distribute the intelligent processing requirements between the digital circuit elements and their real world interconnects in the mixed-signal sensor domain. In this paper we propose the distribution of intelligent processing, or fuselets by three levels of information fusion. These are; perception, fuselets, processing algorithms and neural nets. The proposed robust design methodology for multidisciplinary levels, involves the blending of the s-domain (continuous) and z-domain (digital), resulting in the wp-domain (mixed-signal) models. The advantage of using the wp-domain bilinear transformation for mixed-signal design is the ability to handle the discrete portion of the design like a continuous system, thus unifying the design process for domain distributed intelligent processing systems.

关键词： Intelligent sensors Information systems Clocks Digital circuits Integrated circuit interconnections Sensor systems Neural networks Robustness design methodology Continuous time systems

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Novel radio frequency energy harvesting model

Novel radio frequency energy harvesting model

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2012 IEEE International Power engineering and Optimization Conference, PEOCO 2012

作者： ElAnzeery, Hossam Mahmoud Gamal ElDin Mohammed ElBagouri, Mohamed Abd ElAziz Saad Guindi, Rafik Department of Microelectronics System Design Nanoelectronics Integrated Systems Center Nile University Smart Village B2 Km 28 Cairo-Alex. Desert Road 12677 Cairo Egypt Department of Electrical and Electronics Engineering University of Technology PETRONAS Bandar Seri Iskandar 31750 Tronoh Perak Malaysia

ISBN: (纸本)9781467306614

Energy and Environment, both are the main concern for every researcher allover the world. Alternative energy sources that are environmental friendly became the challenge to satisfy world needs. Oil and Gas are no more the main source of Energy, consequently the demand of an everlasting cheap source of energy that is environmental friendly, is the main goal recently. During the last decade, power consumption has decreased opening the field for energy harvesting to become a real time solution for providing different sources of electrical power. Energy Harvesting is a new technology that is going to make a revolution in the coming decade. Energy Harvesting is a technique to provide alternative sources of energy that are environmental friendly and low in cost. Future applications need wireless devices to operate for longer durations away from centralized power sources or the amount of power that can be supplied to these wireless devices to be increased. Currently, many technologies have been developed that attempt to overcome the limitations imposed on wireless devices. Radio Frequency Energy Harvesting is one of these types of energy harvesting that is able to convert Radio Frequency waves from ambient air to electrical energy. This paper presents a model for harvesting radio frequency energy waves. The presented model is directed towards different applications and targeting mainly Radio Frequency Identification (RFID) applications, where it works on frequencies in the range of 2.1 - 2.45 GHz. The recommended model faces size and efficiency problems presenting a very small radio frequency energy-harvesting model that can be implemented easily inside Radio Frequency Identification (RFID) applications. A final model for Radio Frequency Energy Harvesting is proposed based on different types of simulations and experiments. © 2012 IEEE.

关键词： Energy harvesting

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Paradigm of design for biosystem-on-a-chip(BioSoC)

Paradigm of design for biosystem-on-a-chip(BioSoC)

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IEEE International Conference on Microelectronic systems Education

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

The paradigm of design for biosystem-on-a-chip (BioSoC), is that multidisciplinary skills are required. Thus, the educational goals are to develop an understanding of micro/macro collaboration along with the ability to apply and use multidisciplinary skills for the design and performance evaluation of a "biosystem on a chip". The need for the architectural design of the BioSoC addresses the next-generation of intelligent information processing systems.

关键词： Intelligent sensors Collaboration design engineering Biology computing Chemical and biological sensors Biosensors Artificial intelligence microelectronics Circuits Chemical sensors

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Continuous-time digital twin with analog memristive neural ordinary differential equation solver

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Science Advances 2025年第22期11卷

作者： Hegan Chen Jichang Yang Jia Chen Songqi Wang Shaocong Wang Dingchen Wang Xinyu Tian Yifei Yu Xi Chen Yinan Lin Qifan Zhu Yangu He Xiaoshan Wu Yi Li Xinyuan Zhang Ning Lin Meng Xu Xumeng Zhang Xiaojuan Qi Zhongrui Wang Han Wang Dashan Shang Qi Liu Kwang-Ting Cheng Ming Liu Department of Electrical and Electronic Engineering the University of Hong Kong Hong Kong China. School of Microelectronics Southern University of Science and Technology Shenzhen 518055 China. Center for Advanced Semiconductors and Integrated Circuits the University of Hong Kong Hong Kong China. Department of Electronic and Computer Engineering the Hong Kong University of Science and Technology Hong Kong China. School of Integrated Circuits Hubei Key Laboratory for Advanced Memories Huazhong University of Science and Technology Wuhan 430074 China. State Key Laboratory of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University Shanghai 200433 China. State Key Lab of Fabrication Technologies for Integrated Circuits and Key Laboratory of Microelectronic Devices & Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing 100029 China. University of Chinese Academy of Sciences Beijing 100049 China.

Digital twins, which replicate real-world entities through computational models, are transforming manufacturing and automation. While recent advances in machine learning have enabled data-driven digital twin development using discrete-time data and finite-depth models on digital hardware, these approaches face significant limitations. They struggle to capture continuous-time dynamics and model complex systems, and suffer from substantial time and energy overheads due to physically separated storage and processing as well as frequent analog-digital (A/D) conversions. Here, we propose a memristive neural ordinary differential equation (ODE) solver for digital twins. Our approach is intrinsically time-continuous using infinite-depth neural networks to model complex dynamics. Fully analog memristor arrays collocate storage and computation, addressing the von Neumann bottleneck and reducing A/D conversion requirements. We experimentally validate our solver on digital twins of HP variable-resistor model and Lorenz96 dynamics, demonstrating a 166.5-fold/369.3-fold speedup and a 499.0-fold/673.9-fold improvement in energy efficiency, respectively. This work paves the way to future digital twins for Industry 4.0.

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