paul hasler thesis

Group by: Degree Date (Year Only) | Authors | No GroupingNumber of items: 47.2000 Siegel, Micah Seth (2000) Genetically engineered sensors of cell signaling. Dissertation (Ph.D.), California Institute of Technology. 1997 Boahen, Kwabena Adu (1997) Retinomorphic vision systems : reverse engineering the vertebrate retina. Dissertation (Ph.D.), California Institute of Technology. Diorio, Christopher J. (1997) Neurally inspired silicon learning : from synapse transistors to learning arrays. Dissertation (Ph.D.), California Institute of Technology. Hasler, Paul Edward (1997) Foundations of learning in analog VLSI. Dissertation (Ph.D.), California Institute of Technology. Liu, Shih-Chii (1997) Neuromorphic models of visual and motion processing in the fly visual system. Dissertation (Ph.D.), California Institute of Technology. Minch, Bradley Arthur (1997) Analysis, synthesis, and implementation of networks of multiple-input translinear elements. Dissertation (Ph.D.), California Institute of Technology. Sarpeshkar, Rahul (1997) Efficient precise computation with noisy components : extrapolating from an electronic cochlea to the brain. Dissertation (Ph.D.), California Institute of Technology. 1994 Ryckebusch, Sylvie Adrienne (1994) The central nervous control of walking in the locust, Schistocerca Americana. Dissertation (Ph.D.), California Institute of Technology. 1993 Kerns, Douglas A. (1993) Experiments in.
Distinctions:  2011 Georgia Tech Outstanding Doctoral Thesis Advisor Award 2002 Office of Naval Research Young Investigator. Paul Raphorst best paper award, IEEE Electron Devices Society, 1997 Finalist for the Packard Foundation Young Investigator Fellowships Guest Editor for special issue on Floating-Gate Circuits and Systems in IEEE Transactions on Circuits and Systems II. Summer 2000 Organizing Session Co-chair, Silicon Learning Systems, International Conference on Circuits and Systems, Monterey, 1998 Organizing Session Chair: Floating-Gate Devices and Circuits, International Conference on Circuits and Systems, Orlando, 1999 Organizing Session Chair (Invited), Floating-Gate and Neuromorphic Circuits, Midwest Circuits and Systems, Las Cruces, NM, 1999 NSF Career Award, Analog VLSI Integrated Circuits for Real-Time Control Paul Hasler, Bradley A. Minch, and Chris Diorio, An Autozeroing Floating-Gate Amplifier,'' IEEE Transactions on Circuits and Systems II in Press. Paul Hasler, Continuous-Time Feedback in Floating-Gate MOS Circuits,'' IEEE Transactions on Circuits and Systems II, in Press. C. Diorio, J. Dugger, Paul Hasler, B.A. Minch: Adaptive Circuits and Synapses Using pFET Floating-Gate Devices, in Gert Cauwenbergs Learning in Silicon, Kluwer Acdemic, pp. 33-65, 1999. Paul Hasler and Jeff Dugger, Correlation Learning Rule in Floating-Gate pFET Synapses, IEEE Transactions on Circuits and Systems II, in Press. Matt Kucic, AiChen Low, Paul Hasler, and Joe Neff, A Programmable Continuous-time Floating-Gate Fourier Processor,'' IEEE Transactions on Circuits and Systems II, in Press. Paul Hasler, Bradley A. Minch, Jeff Dugger, and Chris Diorio, Adaptive Circuits and Synapses Using pFET Floating-Gate Devices, in Gert Cauwenbergs, Learning in Silicon, Kluwer Acdemic Publisher, 1999, pp. 33-65. A. Apsel, Paul E. Hasler, T. Stanford: An Adaptive Front End for Olfaction.
AbstractNOTE: Text or symbols not renderable in plain ASCII are indicated by [.]. Abstract is included in.pdf document.Floating-gate technology can be used to build silicon systems that adapt and learn. This technology is well suited to implement adaptation and learning because we are not building analog EEPROMS, but rather circuit elements with important time domain dynamics. These floating-gate circuits use the hot-electron-injection, electron-tunneling, and drain-induced-barrier-lowering phenomena in a standard submicron CMOS process. This technology works with the constraints of the silicon medium, and is similar to biological systems that turned potential liabilities into features.I develop the first analytical model of the impact-ionization and hot-electron processes in MOS devices by solving for a self-consistent distribution function from the spatially varying Boltzmann transport equation. From this electron distribution function, the probabilities of impact ionization and hot-electron injection are calculated as functions of channel current, drain voltage, and floating-gate voltage. The analytical model simultaneously fits both the hot-electron-injection and impact-ionization data. These analytical results yield measurements of the energy-dependent impactionization collision rate that is consistent with numerically calculated collision rates reported in the literature.I describe the design, fabrication, characterization, and modeling of an array of single-transistor synapses that simultaneously store the weight value, compute the product of the input and floating gate value, and update the weight value according to a hebbian or backpropagation learning rule. Circuits with one floating-gate synapse exhibit a range of possible stabilizing and destabilizing behaviors, and circuits with multiple-synapses show examples of competitive and cooperative behavior. By.