J. Douglas Birdwell

Bio: J. Douglas Birdwell is an academic researcher from University of Tennessee. The author has contributed to research in topics: Artificial neural network & Load balancing (computing). The author has an hindex of 18, co-authored 44 publications receiving 1422 citations.

A Survey of Neuromorphic Computing and Neural Networks in Hardware.

Abstract: Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices, and models that contrast the pervasive von Neumann computer architecture This biologically inspired approach has created highly connected synthetic neurons and synapses that can be used to model neuroscience theories as well as solve challenging machine learning problems The promise of the technology is to create a brain-like ability to learn and adapt, but the technical challenges are significant, starting with an accurate neuroscience model of how the brain works, to finding materials and engineering breakthroughs to build devices to support these models, to creating a programming framework so the systems can learn, to creating applications with brain-like capabilities In this work, we provide a comprehensive survey of the research and motivations for neuromorphic computing over its history We begin with a 35-year review of the motivations and drivers of neuromorphic computing, then look at the major research areas of the field, which we define as neuro-inspired models, algorithms and learning approaches, hardware and devices, supporting systems, and finally applications We conclude with a broad discussion on the major research topics that need to be addressed in the coming years to see the promise of neuromorphic computing fulfilled The goals of this work are to provide an exhaustive review of the research conducted in neuromorphic computing since the inception of the term, and to motivate further work by illuminating gaps in the field where new research is needed

Method and apparatus for predicting object properties and events using similarity-based information retrieval and modeling

Abstract: Method and apparatus for predicting properties of a target object comprise application of a search manager for analyzing parameters of a plurality of databases for a plurality of objects, the databases comprising an electrical, electromagnetic, acoustic spectral database (ESD), a micro-body assemblage database (MAD) and a database of image data whereby the databases store data objects containing identifying features, source information and information on site properties and context including time and frequency varying data. The method comprises application of multivariate statistical analysis and principal component analysis in combination with content-based image retrieval for providing two-dimensional attributes of three dimensional objects, for example, via preferential image segmentation using a tree of shapes and to predict further properties of objects by means of k-means clustering and related methods. By way of example, one of a criminal activity and a fraudulent activity event, an intrusion event and a fire event and residual objects may be predicted and located and qualified such that, for example, properties of the residual objects may be qualified, for example, via black body radiation and micro-body databases including charcoal assemblages.

Patient permission-based mobile health-linked information collection and exchange systems and methods

Abstract: A suite of components comprising an objective measurement medical data collection device and a cohort database may standardize, simplify, and objectify clinical outcomes tracking, culminating in population health measurements within the restorative neurosciences such as Parkinson disease individuals diagnosed with a disease. A data collection device may comprise one or more of a gyroscope, an accelerometer, a locator, a camera and a magnetometer for collecting, for example, data related to tremors experienced by the individuals diagnosed with disease and receive instruction data responsive to evaluation of the collected data in relation to the cohort database. A related method collects objective measurements during phases of treatment such as preoperative symptomatology, probabilistic atlas linked targeting for neuromodulation, accountancy for gravitational effects of brain shift during surgery, measurements of movement and quality of life during supervised treatment and ongoing community and self-directed treatment and provides feedback to implants, intelligent devices and users thereof.

Least-square deconvolution: a framework for interpreting short tandem repeat mixtures.

Abstract: Interpreting mixture short tandem repeat DNA data is often a laborious process, involving trying different genotype combinations mixed at assumed DNA mass proportions, and assessing whether the resultant is supported well by the relative peak-height information of the mixture sample. If a clear pattern of major-minor alleles is apparent, it is feasible to identify the major alleles of each locus and form a composite genotype profile for the major contributor. When alleles are shared between the two contributors, and/or heterozygous peak imbalance is present, it becomes complex and difficult to deduce the profile of the minor contributor. The manual trial and error procedures performed by an analyst in the attempt to resolve mixture samples have been formalized in the least-square deconvolution (LSD) framework reported here for two-person mixtures, with the allele peak height (or area) information as its only input. LSD operates on the peak-data information of each locus separately, independent of all other loci, and finds the best-fit DNA mass proportions and calculates error residual for each possible genotype combination. The LSD mathematical result for all loci is then to be reviewed by a DNA analyst, who will apply a set of heuristic interpretation guidelines in an attempt to form a composite DNA profile for each of the two contributors. Both simulated and forensic peak-height data were used to support this approach. A set of heuristic guidelines is to be used in forming a composite profile for each of the mixture contributors in analyzing the mathematical results of LSD. The heuristic rules involve the checking of consistency of the best-fit mass proportion ratios for the top-ranked genotype combination case among all four- and three-allele loci, and involve assessing the degree of fit of the top-ranked case relative to the fit of the second-ranked case. A different set of guidelines is used in reviewing and analyzing the LSD mathematical results for two-allele loci. Resolution of two-allele loci is performed with less confidence than for four- and three-allele loci. This paper gives a detailed description of the theory of the LSD methodology, discusses its limitations, and the heuristic guidelines in analyzing the LSD mathematical results. A 13-loci sample case study is included. The use of the interpretation guidelines in forming composite profiles for each of the two contributors is illustrated. Application of LSD in this case produced correct resolutions at all loci. Information on obtaining access to the LSD software is also given in the paper.

On Reliable Control System Designs

Abstract: A research effort is summarized which addresses some of the current problems in interfacing systems theory and reliability. Reliability is roughly the probability that a system will perform according to specifications for a given amount of time. The reliability of a system depends on the structure of its components. Systems theory and control theory deal with the response characteristics of a system, which depend on the system dynamics. The concepts necessary to unify the structural and the dynamic properties of a system are defined. The result is a definition of what constitutes a reliable system, from the viewpoint of systems theory, and a methodology which can be used to determine if a given design allows a reliable control system design.

Principles of Neural Science

Abstract: I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Intuitive computing methods and systems

Abstract: A smart phone senses audio, imagery, and/or other stimulus from a user's environment, and acts autonomously to fulfill inferred or anticipated user desires. In one aspect, the detailed technology concerns phone-based cognition of a scene viewed by the phone's camera. The image processing tasks applied to the scene can be selected from among various alternatives by reference to resource costs, resource constraints, other stimulus information (e.g., audio), task substitutability, etc. The phone can apply more or less resources to an image processing task depending on how successfully the task is proceeding, or based on the user's apparent interest in the task. In some arrangements, data may be referred to the cloud for analysis, or for gleaning. Cognition, and identification of appropriate device response(s), can be aided by collateral information, such as context. A great number of other features and arrangements are also detailed.