Biological in forma tion-processing systems operate on completely different principles from those with which most engineers are familiar. For many problems, particularly those in which the input data are ill-conditioned and the computation can be specified in a relative manner, biological solutions are many orders of magnitude more effective than those we have been able to implement using digital methods. This advantage can be attributed principally to the use of elementary physical phenomena as computational primitives, and to the representation of information by the relative values of analog signals, rather than by the absolute values of digital signals. This approach requires adaptive techniques to mitigate the effects of component differences. This kind of adaptation leads naturally to systems that learn about their environment. Large-scale adaptive analog systems are more robust to component degredation and failure than are more conventional

The new generation of silicon retinae has two defining characteristics. First, these synthetic retinae are morphologically equivalent to their biological counterparts---at an appropriate level of abstraction. Second, they accomplish all four major operations performed by biological retinae using neurobiological principles: (1) continuous sensing for detection, (2) local automatic gain control for amplification, (3) spatiotemporal bandpass filtering for preprocessing, and (4) adaptive sampling for quantization. I introduce the term retinomorphic to refer to this subclass of the neuromorphic electronic systems [30]. I compare and contrast their design principles with the standard practice in imager design. I argue that neurobiological principles are best suited to perceptive systems [43] that go beyond reproducing the dynamic scene, like a conventional video camera does, to extracting salient information in real time [3]. I shall present results from a fully operational retinomorphic vis...

This paper provides an overview of research developments toward nanometer-scale electronic switching devices for use in building ultra-densely integrated electronic computers. Specifically, two classes of alternatives to the field-effect transistor are considered: 1) quantum-effect and single-electron solid-state devices and 2) molecular electronic devices. A taxonomy of devices in each class is provided, operational principles are described and compared for the various types of devices, and the literature about each is surveyed. This information is presented in nonmathematical terms intended for a general, technically interested readership

To my parents Yueying and Fugui, for bring me to this beautiful world To my friends, for making my life vivid To my wife Jessie, for your endless love and patience To my daughter Lillian, for the joy you bring to us everydayACKNOWLEDGMENTS I would like to gratefully and sincerely thank Dr. Csaba Andras Moritz for his guidance, understanding and patience throughout my graduate study at Umass Amherst. His mentorship was paramount in providing a well rounded experience consistent to my long-term career goals. He encouraged me to not only grow as a programmer but also as an independent thinker. For everything you’ve done for me, Dr. Moritz, I thank you. I would also like to thank the former and present members of the NASIC research group, especially Pritish Narayanan, Michael Leuchtenburg, Dr. Yao Guo and Dr. Mahmoud Ben Naser, for their consistent help during my PhD study. The friendship with them will never fade with time. I would like to thank the Electrical and Computer Engineering Department of Umass Amherst for the support, which turns my dream into reality. In addition, I would

I describe a vision system that uses neurobiological principles to perform all four major operations found in biological retinae: (1) continuous sensing for detection, (2) local automatic gain control for amplification, (3) spatiotemporal bandpass ltering for preprocessing, and (4) adaptive sampling for quantization. All four operations are performed at the pixel level. The system includes a random-access time-division multiplexed communication channel that reads out asynchronous pulse trains from a 64 64 pixel array in the imager chip, and transmits them to corresponding locations on a second chip that has a64 64 array ofintegrators. Both chips are fully functional. I compare and contrast the design principles of the retina with the standard practice in imager design and analyze the circuits used to amplify, filter, and quantize the visual signal, with emphasis on the performance trade-offs inherent in the circuit topologies used.