John G Harris - US grants

This research deals with the implementation of continuous-time analog VLSI chaps for processing of sensory signals. Two specific analog sensors are being developed: 1) a single-chip visual time- to-contact sensor that reports the amount of time until the chip collides with an oncoming obstacle (assuming constant relative motion), and, 2) a sound localization chip that computes the direction (in two-dimensions) of a sound source using signals from two microphones. Though these projects may appear to be unrelated, the proposed solutions using adaptive analog computation in CMOS hardware lead to many common problems that must be solved. By providing a cross-fertilization between auditory and visual processing, it is hoped that the underlying biological computational primitives and neuronal representations will be discovered. The resulting low-power analog devices have obvious applications in such areas as collision warning sensors for intelligent automobiles and improved, low-power hearing aids. The educational plan at both the undergraduate and graduate level has a strong interdisciplinary emphasis. Too often students are taught to specialize in a narrow area and are consequently unable to relate their work to an overall system objective. Teaching objectives are: 1) to stress the interdisciplinary nature of real- world systems, and 2) to introduce students to problem solving techniques for real-world signal-processing applications. In existing classes, the use of laboratories and computer experiments where students can do hands-on experimentation with concepts is emphasized. New courses at the undergraduate and graduate levels that give students more exposure to real-world experimentation in laboratories will be designed.

The goal of this CRCD project at the University of Florida, entitled, "A Net-Centric Undergraduate Course in Adaptive Systems," is to innovate the engineering undergraduate curriculum by developing a net-centric, WEB based upper division elective on Adaptive Systems. The ultimate goal is to establish a resource center for Adaptive Systems undergraduate instruction at the University of Florida which will integrate collaborations from experts worldwide and will deliver the course locally and distribute it across the WEB to learners at other Universities and in Industry. The software tools and the teaching methodologies developed during this project will be widely applicable to other technological courses, so they transcend the specific area of Adaptive Systems.

9900394
Principe

The focus of this research is the development and evaluation of a new class of algorithms for information
theoretic learning (ITL). Conventional learning designs are usually based on an effort to minimize either square error or a measure of entropy which can be computationally difficult to handle. This project will attempt to estimate and use a new measure of entropy, based on concepts from Renyi. The appeal of the algorithm is that it can be easily integrated with a Parzen window estimator yielding several practical criteria to adapt universal mappers, either under unsupervised or supervised paradigms.

If the research is successful a novel and quite general class of algorithms will be made available to
the scientific community interested in studying and applying learning systems. The natural goal of this research is to further develop the ITL algorithms, an study their application to a variety of important problems in learning. Specifically, the project will study the properties of the estimator for both entropy and mutual information, ways to decrease the computational complexity of the algorithm, extend it to time signals, set its parameter and access its scalability. It will also investigate new distance measures for mutual information optimization and the feasibility of imple-menting an "entropy chip" in analog VLSI which will use the laws of physics to do the computation.

The research team/will be investigating issues in information filtering, independent component analysis and blind source separation using the newly developed ITL class of algorithms. These areas are important in their own right, and have a momentum that will be further advanced in this research. But the team will also use the common computational infra-structure of estimating entropy and mutual information from examples to compare the proposed ITL algorithms' performance with the best available techniques in each field. Specifically, (1) They will extend the present state-of-the-art in the blind source separation of convolutive mixtures. They will apply the new
learning algorithm to the co-channel interference in mobile communication channels, and noise reduction in hearing aids. (2) They will apply ITL to system identification and dynamic modeling and com-pare it to our previous results using the mean square error. (3) The problem of sparse representa-tions is crucial to understand the brain and design intelligent artificial systems. We will be researching how to learn sparse representation from data, using both overcomplete bases and the ITL algorithm to implement independent component analysis.
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Abstract


Proposal Title: XYZ on a Chip: A Nanomaterials/Nanoelectrochemical Route for Communication Between Biochemical Processes and IC Chips
Proposal Number: CTS-0087676
Principal Investigator: Charles Martin
Institution: University of Florida


The development of arrays of electrochemical sensors based on nanomaterials to detect different analytes is to be demonstrated with biosensors. The unique aspect of this project is that the transduction of the binding event is accomplished directly on the chip. The team will develop processes based on redox sensors and electrochemical oligonucleotide sensors. Technical challenges include confinement of sensing elements to micron dimensions, signal transduction, and device control and signal processing. The proposed work in electrochemical sensor technology will establish an interface between electronics and electrolytes. A means to isolate and confine biochemical processes on chips for making amperometric measurements will be developed. Novel microelectrode configurations, previously developed by the PI, will be utilized in an array format for rapid assay experiments. The development of an on-chip potentiostat is proposed. Integration of an onboard controller, integrated circuit, and sensor is planned. This effort to provide electrical communication between biochemical processes and integrated-circuit technology may have applications in molecular electronics, biosensors, and bioartificial organs. The proposed work will complement the NSF Engineering Research Center at their institution. This project is co-funded by the Engineering Education and Centers Division.

EIA-0135946
Fortes, Jose A
University of Florida

ITR/SY: Design and Simulation of Biologically inspired Nanolattice






This joint project between the University of Florida and Purdue University is pursuing scientific principles for designing and engineering biologically inspired neuromorphic computing architectures using radically new molecular electronic devices and biologically inspired, ultra-dense, self-assembled systems. Examples of applications of these architectures include unprecedently small and inexpensive nanoscale intelligent sensors. The architectures can be used to implement neurocomputing models and are well suited for nanotechnologies, thus accelerating the development of useful nanotechnology by providing clear functional targets for nanodevices.
The team of investigators includes computer architects, neurocomputing experts and device physicists working in close collaboration along three highly synergistic thrusts. One of the two thrusts is focused on advancing the understanding of biologically-inspired dynamic information processing systems in order to understand the impact of constraints imposed by architectures and technologies on the properties of these systems. Another thrust investigates neurocomputing system architectures that can be engineered within the constraints of nanotechnologies. The third thrust develops a toolbox of novel mechanisms for integration, self-assembly and interconnection of nanoscale devices.
The architectures are investigated via formal methods and simulation. Internet resources are used to conduct simulation, and to disseminate models, software and other research results. A new course, summer internships and educational materials are being developed to educate students on the key interdisciplinary aspects and results of the project.

0541241
PI: John G. Harris
University of Florida

A Spike-Based Computer Architecture for Sensory Processing

The PIs will develop, study, and build a neurobiologically inspired architecture based on neuronal spikes (or action potentials). The proposed architecture combines previous spike-based sensory processing ideas developed by the PIs with a compelling model of brain computation called the Liquid State Machine (LSM). This model provides a conceptual framework for working with biologically realistic pulsed neuron models (integrate-and-fire neurons) as the basic computational element within a recurrent nonlinear architecture. The PIs propose three key steps for developing networks of spiking processing elements that are useful for computation:
1. The PIs will develop a sampling theory for converting continuous variable inputs into aperiodic spike trains (and likewise transform spikes trains back to continuous amplitude signals).
2. Although interesting, the architecture of the LSM can be largely improved once the characteristics of the computation are better understood. In particular, while the interconnect of the liquid is arbitrary and fixed, the PIs plan to develop a theory of adaptation for such spike based representations.
3. The PIs will map the spike-based architecture to todays silicon electronics. This hybrid analog/digital architecture is fundamentally different from both conventional digital architectures and past analog computing devices. However, the proposed architecture will be of only scientific interest if it cannot be built with competitive performance measures in terms of computational capability, power consumption, noise immunity and dynamic range. Therefore, in order to design the architecture in silicon, the PIs will identify key computational principles, design signal transformations, and fabricate the resulting building blocks with huge numbers of sufficiently small components in CMOS technology.
Finally, in order to ground the theoretical research and design in engineering practice, the PIs propose to develop a prototype system for chemical sensing using an off-the-shelf electronic nose (or e-nose) as the front end. This application was chosen due to its importance in homeland security, and also because it provides a natural input to the proposed spike-based architecture.

DESCRIPTION (provided by applicant): The overall goal of this project is to design a new generation of fully implantable flexible substrate microelectrode array probes to record neural activity from behaving rodents. In existing approaches, the behaving rodents are either tethered or encumbered by external devices strapped to their bodies. A fully implantable unit would allow improved characterization of brain function via neural recordings in rats in an unrestrained condition. The proposed device is a battery powered electronic chip that utilizes the state-of- the-art integrate-and-fire (IF) representation and proven protocols: microwire array, flexible substrate, and wireless communication. What makes this implantable specification possible is anew IF sampling principle that is able to reduce both the power dissipation and the necessary bandwidth to transmit high-resolution data. We anticipate that it is possible to build an implant that uses less than 2mW of total power dissipation to record, amplify, encode and transmit wirelessly 16 channels of field potentials and extracellular action for 72-96 hours depending on the data rates. An external signal reconstruction algorithm will output neural data with at least 40dB accuracy (better on high amplitude signal regions) at a 20 kHz sampling rate. In order to design, characterize, build and test in vivo the Florida Wireless Implantable Recording Electrodes (FWIRE), we specifically propose: 1. To design, fabricate in VLSI, test in vivo and formulate system specifications for an ultra low power 16- channel amplifier with pulsed output based on the novel integrate-and-fire sampling scheme. The overall power consumption of this subsystem will be below 1mW. 2. To design an ultra-power (1mW), low-bandwidth (500Kpulses/sec) wireless link and integrate the multiple modules (electrodes, integrate-and-fire amplifiers, communication link) into an implantable package using a flexible substrate. 3. To study in vivo the characteristics of FWIRE during the full duration of the implantable probe development. Bottlenecks in the design will be anticipated, found, and corrected;system performance will be fully characterized.

Intellectual Merit
The Smart Grid is among the most important and ambitious engineering endeavors of our time. Deep integration of renewable electricity generation is a key driver of the Smart Grid vision. A fundamental challenge is that these energy sources are highly variable ? they are not dispatchable, experience large and rapid changes, and are difficult to predict. The electricity grid must absorb this variability through a portfolio of solutions that include improved forecasts, demand shaping, electricity storage, optimal grid operations, and new market instruments. Our objective is to analyze this portfolio for wind energy integration. We will develop an analytical framework to study how wind variability can be addressed in competitive electricity markets at deep penetration levels. We will investigate market based wind curtailment, aggregation, matching of variable generation and flexible loads, and novel contract instruments.

Broader Impact
The societal impact of our research comes from the fact that renewable electricity generation is critical for energy security and environmental sustainability. Our research directly addresses the obstacles that must be overcome to significantly increase the penetration of renewable generation. The technological impact of our research will stem from our novel framework to analyze existing options and design novel mechanisms for renewable integration. This will offer new insights and analysis methods which will guide the design of optimal portfolios of technology components and coordination mechanisms. The educational impact of our research is derived from our serious efforts at integrating education at all levels with our research. We will equip our students with the multi-disciplinary training in power systems operations, optimization, control, and economics to become leaders in making the Smart Grid vision a reality.

Large-scale critical infrastructure systems, including energy and transportation networks, comprise millions of individual elements (human, software and hardware) whose actions may be inconsequential in isolation but profoundly important in aggregate. The focus of this project is on the coordination of these elements via ubiquitous sensing, communications, computation, and control, with an emphasis on the electric grid. The project integrates ideas from economics and behavioral science into frameworks grounded in control theory and power systems. Our central construct is that of a ?resource cluster,? a collection of distributed resources (ex: solar PV, storage, deferrable loads) that can be coordinated to efficiently and reliably offer services (ex: power delivery) in the face of uncertainty (ex: PV output, consumer behavior). Three topic areas form the core of the project: (a) the theoretical foundations for the ?cluster manager? concept and complementary tools to characterize the capabilities of a resource cluster; (b) centralized resource coordination strategies that span multiple time scales via innovations in stochastic optimal control theory; and (c) decentralized coordination strategies based on cluster manager incentives and built upon foundations of non-cooperative dynamic game theory.

These innovations will improve the operation of infrastructure systems via a cyber-physical-social approach to the problem of resource allocation in complex infrastructures. By transforming the role of humans from passive resource recipients to active participants in the electric power system, the project will facilitate energy security for the nation, and climate change mitigation. The project will also engage K-12 students through lab-visits and lectures; address the undergraduate demand for power systems training through curricular innovations at the intersection of cyber-systems engineering and physical power systems; and equip graduate students with the multi-disciplinary training in power systems, communications, control, optimization and economics to become leaders in innovation.