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Low-power Design of a Neuromorphic IC and MICS TransceiverJanuary 2011 (has links)
abstract: The first part describes Metal Semiconductor Field Effect Transistor (MESFET) based fundamental analog building blocks designed and fabricated in a single poly, 3-layer metal digital CMOS technology utilizing fully depletion mode MESFET devices. DC characteristics were measured by varying the power supply from 2.5V to 5.5V. The measured DC transfer curves of amplifiers show good agreement with the simulated ones with extracted models from the same process. The accuracy of the current mirror showing inverse operation is within ±15% for the current from 0 to 1.5mA with the power supply from 2.5 to 5.5V. The second part presents a low-power image recognition system with a novel MESFET device fabricated on a CMOS substrate. An analog image recognition system with power consumption of 2.4mW/cell and a response time of 6µs is designed, fabricated and characterized. The experimental results verified the accuracy of the extracted SPICE model of SOS MESFETs. The response times of 4µs and 6µs for one by four and one by eight arrays, respectively, are achieved with the line recognition. Each core cell for both arrays consumes only 2.4mW. The last part presents a CMOS low-power transceiver in MICS band is presented. The LNA core has an integrated mixer in a folded configuration. The baseband strip consists of a pseudo differential MOS-C band-pass filter achieving demodulation of 150kHz-offset BFSK signals. The SRO is used in a wakeup RX for the wake-up signal reception. The all digital frequency-locked loop drives a class AB power amplifier in a transmitter. The sensitivity of -85dBm in the wakeup RX is achieved with the power consumption of 320µW and 400µW at the data rates of 100kb/s and 200kb/s from 1.8V, respectively. The sensitivities of -70dBm and -98dBm in the data-link RX are achieved with NF of 40dB and 11dB at the data rate of 100kb/s while consuming only 600µW and 1.5mW at 1.2V and 1.8V, respectively. / Dissertation/Thesis / Ph.D. Electrical Engineering 2011
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