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Electrical and Computer Engineering Faculty Research & Creative Works

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Full-Text Articles in Engineering

Dynamic Simulations Of Cascading Failures, Hong Tao Ma, Badrul H. Chowdhury Jan 2007

Dynamic Simulations Of Cascading Failures, Hong Tao Ma, Badrul H. Chowdhury

Electrical and Computer Engineering Faculty Research & Creative Works

Steady state analysis cannot provide the details of how system evolves in cascading failure. Dynamic response of generator plays an important role in power system operation and blackout events. In this paper, classical generator and detail generator models are integrated into system model for cascading dynamic simulations.. The cascading scenarios are compared using both steady state and dynamic simulations. Classical models are simpler; however, the detailed generator model is more accurate. Generator performance of speed deviation and angle deviations as well as the bus voltage profile are investigated for various scenarios. The IEEE 118-bus, 20-generator test case is used as …

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Near Optimal Neural Network-Based Output Feedback Control Of Affine Nonlinear Discrete-Time Systems, Qinmin Yang, Jagannathan Sarangapani Jan 2007

Near Optimal Neural Network-Based Output Feedback Control Of Affine Nonlinear Discrete-Time Systems, Qinmin Yang, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel online reinforcement learning neural network (NN)-based optimal output feedback controller, referred to as adaptive critic controller, is proposed for affine nonlinear discrete-time systems, to deliver a desired tracking performance. The adaptive critic design consist of three entities, an observer to estimate the system states, an action network that produces optimal control input and a critic that evaluates the performance of the action network. The critic is termed adaptive as it adapts itself to output the optimal cost-to-go function which is based on the standard Bellman equation. By using the Lyapunov approach, the uniformly ultimate boundedness …

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Neural Network Based Method For Predicting Nonlinear Load Harmonics, Joy Mazumdar, Ronald G. Harley, Frank C. Lambert, Ganesh K. Venayagamoorthy Jan 2007

Neural Network Based Method For Predicting Nonlinear Load Harmonics, Joy Mazumdar, Ronald G. Harley, Frank C. Lambert, Ganesh K. Venayagamoorthy

Electrical and Computer Engineering Faculty Research & Creative Works

Generation of harmonics and the existence of waveform pollution in power system networks are important problems facing the power utilities. The increased use of nonlinear devices in industry has resulted in direct increase of harmonic distortion in the industrial power system in recent years. Interaction between loads and sources in a power distribution network is a complex process and often not possible to explain analytically without making assumptions. The determination of true harmonic current distortion of a load is further complicated by the fact that the supply voltage waveform at the point of common coupling (PCC) is rarely a pure …

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Online Reinforcement Learning Neural Network Controller Design For Nanomanipulation, Qinmin Yang, Jagannathan Sarangapani Jan 2007

Online Reinforcement Learning Neural Network Controller Design For Nanomanipulation, Qinmin Yang, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel reinforcement learning neural network (NN)-based controller, referred to adaptive critic controller, is proposed for affine nonlinear discrete-time systems with applications to nanomanipulation. In the online NN reinforcement learning method, one NN is designated as the critic NN, which approximates the long-term cost function by assuming that the states of the nonlinear systems is available for measurement. An action NN is employed to derive an optimal control signal to track a desired system trajectory while minimizing the cost function. Online updating weight tuning schemes for these two NNs are also derived. By using the Lyapunov approach, …

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Optimal Diversity Combining Based On Linear Estimation Of Rician Fading Channels, Jingxian Wu, Chengshan Xiao Jan 2007

Optimal Diversity Combining Based On Linear Estimation Of Rician Fading Channels, Jingxian Wu, Chengshan Xiao

Electrical and Computer Engineering Faculty Research & Creative Works

Optimal receiver diversity combining employing linear channel estimation is examined. Based on the statistical properties of pilot-assisted least-squares (LS) and minimum mean square error (MMSE) channel estimation, an optimal diversity receiver for wireless systems employing practical linear channel estimation on Rician fading channels is proposed. Exact analytical expressions for the symbol error rates of LS and MMSE channel estimation aided optimal diversity combining are derived. It is shown that an MPSK wireless system with MMSE channel estimation has the same SER when the MMSE channel estimation is replaced by LS estimation. This is an interesting counter-example to the common perception …

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Error Performance Of Double Space Time Transmit Diversity Systems, Jingxian Wu, Y. Rosa Zheng, Ashwin Gumaste, Chengshan Xiao Jan 2007

Error Performance Of Double Space Time Transmit Diversity Systems, Jingxian Wu, Y. Rosa Zheng, Ashwin Gumaste, Chengshan Xiao

Electrical and Computer Engineering Faculty Research & Creative Works

The theoretical error performance of double space time transmit diversity (DSTTD) system with optimum combining receiver is analyzed in this paper. by employing both spatial multiplexing and transmit diversity in one system, DSTTD provides practical tradeoff between system spectral efficiency and diversity gain. We derive exact analytical expressions to describe the symbol error rate for DSTTD systems. The effects of both diversity gain and antenna interference introduced by spatial multiplexing are quantified in the results. In addition, the performance of DSTTD system with successive interference cancellation is also investigated. Simulation results are in excellent agreement with the theoretical results obtained …

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Hybrid Ac/Dc Power Distribution Solution For Future Space Applications, Sushant Barave, Badrul H. Chowdhury Jan 2007

Hybrid Ac/Dc Power Distribution Solution For Future Space Applications, Sushant Barave, Badrul H. Chowdhury

Electrical and Computer Engineering Faculty Research & Creative Works

As NASA readies itself for new space exploration initiatives starting with a human return to the Moon by the year 2020 eventually leading to human exploration of Mars, the requirements for a safe and reliable power system will become important issues. A preliminary study of a proposed hybrid AC/DC distribution system with a power electronic interface is investigated. A Static synchronous Compensator (STATCOM) is considered as the power electronic interface between the AC and the DC portions of the hybrid AC/DC distribution system. The system is modeled in EMTDC/PSCAD and tested for certain operating conditions and contingencies. High reliability and …

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Implementation Of Static And Semi-Static Versions Of A Bit-Wise Pipelined Dual-Rail Ncl 2s Complement Multiplier, R. Sankar, V. Kadiyala, Ravi Bonam, S. Kumar, S. Mohan, F. Kacani, Waleed K. Al-Assadi, Scott C. Smith Jan 2007

Implementation Of Static And Semi-Static Versions Of A Bit-Wise Pipelined Dual-Rail Ncl 2s Complement Multiplier, R. Sankar, V. Kadiyala, Ravi Bonam, S. Kumar, S. Mohan, F. Kacani, Waleed K. Al-Assadi, Scott C. Smith

Electrical and Computer Engineering Faculty Research & Creative Works

This paper focuses on implementing a 2s complement 8x8 dual-rail bit-wise pipelined multiplier using the asynchronous NULL Convention Logic (NCL) paradigm. The design utilizes a Wallace tree for partial product summation, and is implemented and simulated in VHDL, the transistor level, and the physical level, using a 1.8V 0.18,um TSMC CMOS process.The multiplier is realized using both static and semi-static Dualversions of the NCL gates; and these two implementations are compared in terms of area, power, and speed.

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Improvement Of Can Bus Performance By Using Error-Correction Codes, Krishna Chaitanya Emani, Maciej Jan Zawodniok, Y. Rosa Zheng, Jagannathan Sarangapani, Keong W. Kam Jan 2007

Improvement Of Can Bus Performance By Using Error-Correction Codes, Krishna Chaitanya Emani, Maciej Jan Zawodniok, Y. Rosa Zheng, Jagannathan Sarangapani, Keong W. Kam

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, two variants of the Hybrid Automatic Repeat Request (HARQ) scheme for CAN bus are presented. The basic HARQ uses error-correction code based on the Reed- Solomon (RS) technique and the Cyclic Redundancy Check (CRC) method to detect errors. The second scheme uses the cyclic error-correction method instead of the CRC error-detection method to further improve the throughput. Moreover, the second scheme uses no additional bit overhead when compared with the basic HARQ scheme. This paper presents the performance of the proposed schemes using MATLAB and NS2 simulations. Experimental data of error patterns were used for realistic evaluation. …

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Multiclass Cancer Classification Using Semisupervised Ellipsoid Artmap And Particle Swarm Optimization With Gene Expression Data, Georgios C. Anagnostopoulos, Donald C. Wunsch, Rui Xu Jan 2007

Multiclass Cancer Classification Using Semisupervised Ellipsoid Artmap And Particle Swarm Optimization With Gene Expression Data, Georgios C. Anagnostopoulos, Donald C. Wunsch, Rui Xu

Electrical and Computer Engineering Faculty Research & Creative Works

It is crucial for cancer diagnosis and treatment to accurately identify the site of origin of a tumor. with the emergence and rapid advancement of DNA microarray technologies, constructing gene expression profiles for different cancer types has already become a promising means for cancer classification. In addition to research on binary classification such as normal versus tumor samples, which attracts numerous efforts from a variety of disciplines, the discrimination of multiple tumor types is also important. Meanwhile, the selection of genes which are relevant to a certain cancer type not only improves the performance of the classifiers, but also provides …

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Near Optimal Output-Feedback Control Of Nonlinear Discrete-Time Systems In Nonstrict Feedback Form With Application To Engines, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier Jan 2007

Near Optimal Output-Feedback Control Of Nonlinear Discrete-Time Systems In Nonstrict Feedback Form With Application To Engines, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier

Electrical and Computer Engineering Faculty Research & Creative Works

A novel reinforcement-learning based output-adaptive neural network (NN) controller, also referred as the adaptive-critic NN controller, is developed to track a desired trajectory for a class of complex nonlinear discrete-time systems in the presence of bounded and unknown disturbances. The controller includes an observer for estimating states and the outputs, critic, and two action NNs for generating virtual, and actual control inputs. The critic approximates certain strategic utility function and the action NNs are used to minimize both the strategic utility function and their outputs. All NN weights adapt online towards minimization of a performance index, utilizing gradient-descent based rule. …

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Optimal Wide Area Controller And State Predictor For A Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley Jan 2007

Optimal Wide Area Controller And State Predictor For A Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley

Electrical and Computer Engineering Faculty Research & Creative Works

An optimal wide area controller is designed in this paper for a 12-bus power system together with a Static Compensator (STATCOM). The controller provides auxiliary reference signals for the automatic voltage regulators (AVR) of the generators as well as the line voltage controller of the STATCOM in such a way that it improves the damping of the rotor speed deviations of the synchronous machines. Adaptive critic designs theory is used to implement the controller and enable it to provide nonlinear optimal control over the infinite horizon time of the problem and at different operating conditions of the power system. Simulation …

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Rfid Instrumentation In A Field Application, Theresa M. Swift, Martha J. Molander, Steve Eugene Watkins Jan 2007

Rfid Instrumentation In A Field Application, Theresa M. Swift, Martha J. Molander, Steve Eugene Watkins

Electrical and Computer Engineering Faculty Research & Creative Works

The behavior of radio-frequency identification (RFID) tags is investigated in a field application. The RFID instrumentation is used to mark the position of point strain sensors in a fiber-reinforced polymer (FRP), short-span bridge. The tags are surface mounted on carbon FRP structural elements and covered with a resin wear layer, i.e. the deck of the bridge. The smart composite bridge was installed in 2000 and serves as a field testbed for various sensor technologies including the RFID tags. The operation of the RFID network is tested in the field and compared to laboratory tags. Specific research issues include long-term survivability …

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Analysis Of Interaction Between A Crystallographically Uniaxial Ferrite Resonator And A Hall-Effect Transducer, Marina Koledintseva, Alexander A. Kitaytsev Jan 2007

Analysis Of Interaction Between A Crystallographically Uniaxial Ferrite Resonator And A Hall-Effect Transducer, Marina Koledintseva, Alexander A. Kitaytsev

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a number of physical phenomena taking place at the interaction of a crystallographically uniaxial ferrite resonator (UFR) with a semiconductor element, such as a Hall-effect transducer (HET), are analyzed. The UFR in this study is in a direct contact with an unpackaged HET. The interaction is studied in the vicinity of the ferromagnetic resonance in the UFR. The analytical model based on the combination of the problem of interaction of an arbitrarily orientated and shaped UFR with electromagnetic field of a multimode transmission line (waveguide) and thermal balance equations is proposed. A number of thermo/electro/magnetic phenomena that …

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Reinforcement Learning Neural-Network-Based Controller For Nonlinear Discrete-Time Systems With Input Constraints, Pingan He, Jagannathan Sarangapani Jan 2007

Reinforcement Learning Neural-Network-Based Controller For Nonlinear Discrete-Time Systems With Input Constraints, Pingan He, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A novel adaptive-critic-based neural network (NN) controller in discrete time is designed to deliver a desired tracking performance for a class of nonlinear systems in the presence of actuator constraints. The constraints of the actuator are treated in the controller design as the saturation nonlinearity. The adaptive critic NN controller architecture based on state feedback includes two NNs: the critic NN is used to approximate the "strategic" utility function, whereas the action NN is employed to minimize both the strategic utility function and the unknown nonlinear dynamic estimation errors. The critic and action NN weight updates are derived by minimizing …

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A Normalized Fractionally Lower-Order Moment Algorithm For Space-Time Adaptive Processing, Y. Rosa Zheng, Genshe Chen, Erik Blasch Jan 2007

A Normalized Fractionally Lower-Order Moment Algorithm For Space-Time Adaptive Processing, Y. Rosa Zheng, Genshe Chen, Erik Blasch

Electrical and Computer Engineering Faculty Research & Creative Works

A new space-time adaptive processing algorithm is proposed for clutter suppression in phased array radar systems. In contrast to the commonly used normalized least mean square (NLMS) algorithm which uses the second order moments of the data for adaptation, the proposed method uses the lower order moments of the data to adapt the weight coefficients. The normalization is also performed based on the data sample dispersion rather than the variance. Processing results using simulated and measured data show that the proposed algorithm converges faster than the NLMS algorithms in Gaussian and non-Gaussian clutter environments. It also provides better clutter suppression …

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A Proportional-Integrator Type Adaptive Critic Design-Based Neurocontroller For A Static Compensator In A Multimachine Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Yamille Del Valle, Ronald G. Harley Jan 2007

A Proportional-Integrator Type Adaptive Critic Design-Based Neurocontroller For A Static Compensator In A Multimachine Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Yamille Del Valle, Ronald G. Harley

Electrical and Computer Engineering Faculty Research & Creative Works

A novel nonlinear optimal controller for a static compensator (STATCOM) connected to a power system, using artificial neural networks, is presented in this paper. The action dependent heuristic dynamic programming, a member of the adaptive critic designs family is used for the design of the STATCOM neurocontroller. This neurocontroller provides optimal control based on reinforcement learning and approximate dynamic programming. Using a proportional-integrator approach, the proposed neurocontroller is capable of dealing with actual rather than deviation signals. Simulation results are provided to show that the proposed controller outperforms a conventional PI controller for a STATCOM in a small and large …

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Adaptive Power Control Protocol With Hardware Implementation For Wireless Sensor And Rfid Reader Networks, Kainan Cha, Jagannathan Sarangapani, David Pommerenke Jan 2007

Adaptive Power Control Protocol With Hardware Implementation For Wireless Sensor And Rfid Reader Networks, Kainan Cha, Jagannathan Sarangapani, David Pommerenke

Electrical and Computer Engineering Faculty Research & Creative Works

The development and deployment of radio frequency identification (RFID) systems render a novel distributed sensor network which enhances visibility into manufacturing processes. In RFID systems, the detection range and read rates will suffer from interference among high-power reading devices. This problem grows severely and degrades system performance in dense RFID networks. Consequently, medium access protocols (MAC) protocols are needed for such networks to assess and provide access to the channel so that tags can be read accurately. In this paper, we investigate a suite of feasible power control schemes to ensure overall coverage area of the system while maintaining a …

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Analysis Of Radiated Emissions From A Printed Circuit Board Using Expert System Algorithms, Yan Fu, Todd H. Hubing Jan 2007

Analysis Of Radiated Emissions From A Printed Circuit Board Using Expert System Algorithms, Yan Fu, Todd H. Hubing

Electrical and Computer Engineering Faculty Research & Creative Works

Three algorithms developed for expert system electromagnetic compatibility tools are used to evaluate a printed circuit board design. The maximum radiated emissions estimated by the algorithms are compared to the measured data for various board configurations. The algorithms identify the most important electromagnetic interference source mechanisms, drawing attention to the design parameters that have the most significant effect on the radiated emissions.

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Comparison Of Nonuniform Optimal Quantizer Designs For Speech Coding With Adaptive Critics And Particle Swarm, Ganesh K. Venayagamoorthy, Wenwei Zha Jan 2007

Comparison Of Nonuniform Optimal Quantizer Designs For Speech Coding With Adaptive Critics And Particle Swarm, Ganesh K. Venayagamoorthy, Wenwei Zha

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents the design of a companding nonuniform optimal scalar quantizer for speech coding. The quantizer is designed using two neural networks to perform the nonlinear transformation. These neural networks are used in the front and back ends of a uniform quantizer. Two approaches are presented in this paper namely adaptive critic designs and particle swarm optimization, aiming to maximize the signal-to-noise ratio. The comparison of these optimal quantizer designs over a bit-rate range of 3-6 is presented. The perceptual quality of the coding is evaluated by the International Telecommunication Union's Perceptual Evaluation of Speech Quality standard

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Coordinated Machine Learning And Decision Support For Situation Awareness, Timothy Draelos, Pengchu Zhang, Donald C. Wunsch, John E. Seiffertt Iv, Gregory Conrad, Nathan Brannon Jan 2007

Coordinated Machine Learning And Decision Support For Situation Awareness, Timothy Draelos, Pengchu Zhang, Donald C. Wunsch, John E. Seiffertt Iv, Gregory Conrad, Nathan Brannon

Electrical and Computer Engineering Faculty Research & Creative Works

For applications such as force protection, an effective decision maker needs to maintain an unambiguous grasp of the environment. Opportunities exist to leverage computational mechanisms for the adaptive fusion of diverse information sources. The current research employs neural networks and Markov chains to process information from sources including sensors, weather data, and law enforcement. Furthermore, the system operator's input is used as a point of reference for the machine learning algorithms. More detailed features of the approach are provided, along with an example force protection scenario.

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Demodulation Of Fiber-Optic Sensors For Frequency Response Measurement, Abdeq M. Abdi, Steve Eugene Watkins Jan 2007

Demodulation Of Fiber-Optic Sensors For Frequency Response Measurement, Abdeq M. Abdi, Steve Eugene Watkins

Electrical and Computer Engineering Faculty Research & Creative Works

The neural-network-based processing of extrinsic Fabry-Perot interferometric (EFPI) strain sensors was investigated for the special case of sinusoidal strain. The application area is modal or cyclic testing of structures in which the frequency response to periodic actuation must be demodulated. The nonlinear modulation characteristic of EFPI sensors produces well-defined harmonics of the actuation frequency. Relationships between peak strain and harmonic content were analyzed theoretically. A two-stage demodulator was implemented with a Fourier series neural network to separate the harmonic components of an EFPI signal and a backpropagation neural network to predict the peak-to-peak strain from the harmonics. The system performance …

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Noise-Robust Automatic Speech Recognition Using A Predictive Echo State Network, Mark D. Skowronski, John G. Harris Jan 2007

Noise-Robust Automatic Speech Recognition Using A Predictive Echo State Network, Mark D. Skowronski, John G. Harris

Electrical and Computer Engineering Faculty Research & Creative Works

Artificial neural networks have been shown to perform well in automatic speech recognition (ASR) tasks, although their complexity and excessive computational costs have limited their use. Recently, a recurrent neural network with simplified training, the echo state network (ESN), was introduced by Jaeger and shown to outperform conventional methods in time series prediction experiments. We created the predictive ESN classifier by combining the ESN with a state machine framework. In small-vocabulary ASR experiments, we compared the noise-robust performance of the predictive ESN classifier with a hidden Markov model (HMM) as a function of model size and signal-to-noise ratio (SNR). The …

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A Precompensation Algorithm For Pwm-Based Digital Audio Amplifiers For Portable Applications, Xiaoxiang Gong, John G. Harris Jan 2007

A Precompensation Algorithm For Pwm-Based Digital Audio Amplifiers For Portable Applications, Xiaoxiang Gong, John G. Harris

Electrical and Computer Engineering Faculty Research & Creative Works

A novel precompensation algorithm for a Pulse Width Modulation (PWM)-based digital audio amplifier has been developed for portable applications. The Straight-Line Segment PWM (SLSPWM) algorithm results in both low-power and low-complexity devices. The division-free version of this algorithm modifies the algorithm by removing the division using a polynomial approximation. Both SLSPWM and Division-Free SLSPWM feature 16-bit quality performance with fewer calculations compared with previous works. © 2007 IEEE.

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Assuring A Complex Safety-Critical Systems Of Systems, Steven C. Beland, Ann K. Miller Jan 2007

Assuring A Complex Safety-Critical Systems Of Systems, Steven C. Beland, Ann K. Miller

Electrical and Computer Engineering Faculty Research & Creative Works

This paper introduces a broad assurance approach for developing a complex, safety-critical System of Systems (SoS) in order to supplement some guidance that exists in the industry today. Drawing on these varied guidance sources for the assurance of specific technologies and others for developing a modern complex system (or SoS), this paper combines these to present objective-Based criteria to assure a complex safety-critical SoS. This guidance can enable a person or team to write a complete objective-Based development assurance plan for a complex safety-critical SoS and create completion criteria to use for recognizing when it is done. Copyright © 2007 …

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Asymptotic Stability Of Nonholonomic Mobile Robot Formations Using Multilayer Neural Networks, Jagannathan Sarangapani, Travis Alan Dierks Jan 2007

Asymptotic Stability Of Nonholonomic Mobile Robot Formations Using Multilayer Neural Networks, Jagannathan Sarangapani, Travis Alan Dierks

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a combined kinematic/torque control law is developed for leader-follower based formation control using backstepping in order to accommodate the dynamics of the robots and the formation in contrast with kinematic-based formation controllers that are widely reported in the literature. A multilayer neural network (NN) is introduced along with robust integral of the sign of the error (RISE) feedback to approximate the dynamics of the follower as well as its leader using online weight tuning. It is shown using Lyapunov theory that the errors for the entire formation are asymptotically stable and the NN weights are bounded as …

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Spike-Based Feature Extraction For Noise Robust Speech Recognition Using Phase Synchrony Coding, Ismail Uysal, Harsha Sathyendra, John G. Harris Jan 2007

Spike-Based Feature Extraction For Noise Robust Speech Recognition Using Phase Synchrony Coding, Ismail Uysal, Harsha Sathyendra, John G. Harris

Electrical and Computer Engineering Faculty Research & Creative Works

We propose a noise robust feature extraction technique for speech signals using phase synchrony. The front-end employs a psychoacoustic cochlea model with inner hair cells to transform speech into a parallel stream of spike trains as observed in the auditory nerve fibers. The degree of phase synchrony among nerve fibers with similar characteristic frequencies is calculated to yield a feature vector which shows little degradation in response to increasing levels of noise. As a benchmark, the feature set is used in a biologically plausible model with a spike-based, liquid state machine classifier for a simple acoustic classification task. Though applied …

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Florida Wireless Implantable Recording Electrodes (Fwire) For Brain Machine Interfaces, Rizwan Bashirullah, John G. Harris, Justin C. Sanchez, Toshikazu Nishida, Jose C. Principe Jan 2007

Florida Wireless Implantable Recording Electrodes (Fwire) For Brain Machine Interfaces, Rizwan Bashirullah, John G. Harris, Justin C. Sanchez, Toshikazu Nishida, Jose C. Principe

Electrical and Computer Engineering Faculty Research & Creative Works

This paper reviews on-going efforts towards the development of the Florida Wireless Implantable Recording Electrodes (FWIRE). The FWIRE microsystem platform is a fully implantable flexible substrate microelectrode array that employs state-of-the-art integrate-and-fire (IF) signal representation and wireless interface circuitry for recording neural activity from behaving rodents. The modular nature of the implantable neural recording electrode allows future enhancements to be seamlessly added to improve functionality including but not limited to rechargeability through inductive coupling, custom microelectrode arrays, higher capacity batteries, and more advanced integrated circuit technologies. This paper concentrates on custom integrated circuits such as neural interfacing amplifiers, baseband signal …

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A Pitch Estimation Algorithm Based On The Smooth Harmonic Average Peak-To-Valley Envelope, Arturo Camacho, John G. Harris Jan 2007

A Pitch Estimation Algorithm Based On The Smooth Harmonic Average Peak-To-Valley Envelope, Arturo Camacho, John G. Harris

Electrical and Computer Engineering Faculty Research & Creative Works

We propose SHAPE, a novel pitch estimation algorithm (PEA) that builds upon previous PEAs, addressing and solving some of their limitations. The SHAPE algorithm estimates the pitch using a smooth function to compute the average peak to valley distance at harmonic locations. This is done by performing an integral transform over the square-root magnitude of the spectrum using a truncated decaying cosine as a kernel. SHAPE was designed to both match human perception particularly for inharmonic sounds and to be competitive with numerous other PEAs as demonstrated on a common database. © 2007 IEEE.

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Numerical Analysis Of Sandwiched Composite-Fss Structures, Qiang Rui, Chen Ji, Huang Jingyu, Maria Koledintseva, Richard E. Dubroff, James L. Drewniak, Yang Fan Dec 2006

Numerical Analysis Of Sandwiched Composite-Fss Structures, Qiang Rui, Chen Ji, Huang Jingyu, Maria Koledintseva, Richard E. Dubroff, James L. Drewniak, Yang Fan

Electrical and Computer Engineering Faculty Research & Creative Works

A numerical technique to analyze shielding effectiveness of sandwiched FSS-composite structures is proposed. This technique is based on using a dispersive FDTD method in conjuncture with a novel periodic boundary condition to model sandwiched FSS-composite elements. Results show that by inserting single or multilayered FSS elements into composite materials, better shielding effectiveness can be achieved. © 2006 IEEE.

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