Sheng-Feng Yen

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We present the first microwave measurements of the dynamical impedance of an individual, electrically contacted single walled carbon nanotube. Both semiconducting and metallic nanotubes are measured. Using a semiconducting nanotube, we construct an LC nano-resonator at 2 GHz. The Q of the nano-resonator can be tuned by varying the back-gate voltage on the(More)
A neuronal recording system for brain-machine interfaces (BMI) based on asynchronous biphasic pulse coding is described. A recording experiment comparing, in parallel, a commercial recording system (Tucker-Davis Technology) and the UF's custom solution (FWIRE) is set up to compare performance. The novel aspect of the UF system is that the analog signal is(More)
This research investigates a novel data reduction scheme using adaptive leaky refractory integrate-and-fire (ALRIF) neurons to generate pulses for an implanted neural recording system in wireless transmission applications. The wireless implanted multi-channel recording system imposes many constraints on the system but the major constraint is on low(More)
We propose to improve the spatial resolution of electroencephalography (EEG) using a differential recording methodology. Conventional EEG (CEEG) systems independently amplify and digitize the signal from each electrode. The Differential EEG (DEEG) approach amplifies the minute difference signal between neighboring electrodes which greatly eases the burden(More)
A neuronal recording system for brain-machine interfaces (BMI) based on asynchronous biphasic pulse coding is described. It demonstrates the first step in the development of a complete implanted wireless solution with fully integrated circuit architecture. A recording experiment comparing in parallel a commercial recording system (Tucker-Davis Technology(More)
A neuronal recording system for brain-machine interfaces (BMI) based on asynchronous biphasic pulse coding is described. It demonstrates the first step in the development of a completely implanted wireless solution with a fully integrated circuit architecture. A recording experiment comparing, in parallel, a commercial recording system (Tucker-Davis(More)
We present a low-bandwidth analog circuit for implementing an adaptive biphasic leaky integrate-and-fire neuron. This neuron circuit is targeted for signal compression in neural recording applications. Unlike other adaptive neuron circuits, this adaptive integrate-and-fire neuron supports signal reconstruction with known threshold voltages. Matlab(More)
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