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Showing 1 to 8 of 8 for “"Neural Signal Processing"”.

  1. Reconfigurable System-on-Chip Architecture for Neural Signal Processing

    … is tied to the efficiency of its individual processing elements such as spike detection, sorting and decoding. To achieve reliable operation, BMIs are equipped with hundreds of electrodes at the neural interface. While a single electrode/tetrode communicates with up to four neurons at a given …

    temple Repository record for Reconfigurable System-on-Chip Architecture for Neural Signal Processing (opens in a new tab)

  2. Generative models for neural time series with structured domain priors

    … to research in the intersection of statistical signal processing and neuroscience (neural signal processing), my research advisor, Professor Emery N. Brown, explained at length that the signals from seemingly complex neural/biological systems are not purely random, but rather those that have …

    mit Repository record for Generative models for neural time series with structured domain priors (opens in a new tab)

  3. Representation Learning on Large-Scale Neural and Healthcare Data: A Practitioner’s Perspective

    … both critical and practical challenges in neural signal processing and healthcare predictive modeling. For neural signal processing, we first strive to bridge the gap of the fast-increasing scale of data acquisition in neural recording and the limited bandwidth of data links for …

    umn Repository record for Representation Learning on Large-Scale Neural and Healthcare Data: A Practitioner’s Perspective (opens in a new tab)

  4. Developing a Neural Signal Processor Using the Extended Analog Computer

    Neural signal processing to decode neural activity has been an active research area in the last few decades. The next generation of advanced multi-electrode neuroprosthetic devices aim to detect a multiplicity of channels from multiple electrodes, making the relatively time-critical processing

    iupui Repository record for Developing a Neural Signal Processor Using the Extended Analog Computer (opens in a new tab)

  5. The Mechanisms And Roles Of Feedback Loops For Visual Processing

    Signal flow in the brain is not unidirectional; feedback represents a key element in neural signal processing. To address the question on how do neural feedback loops work in terms of synapses, microcircuitry, and systems dynamics, we developed a chick midbrain slice preparation to study and …

    wustl Repository record for The Mechanisms And Roles Of Feedback Loops For Visual Processing (opens in a new tab)

  6. Design Techniques for Embedded Computer Vision and Signal Processing

    … systems for embedded computer vision and signal processing. The techniques are developed to address concerns of real-time processing efficiency and energy efficiency under resource-constrained operation as well accuracy considerations, which are conventionally associated with the …

    maryland Repository record for Design Techniques for Embedded Computer Vision and Signal Processing (opens in a new tab)

  7. NANOSTRUCTURED COMPOSITE FILMS FOR BRAIN-MACHINE INTERFACE APPLICATIONS

    … technologies, fostering information flow and processing between natural and artificial components [1] are essential for developing energy-efficient, compact interfaces that integrate bioelectrical activity for personalized medicine. In this frame, advances in thin-film sensors and non-invasive …

    milano Repository record for NANOSTRUCTURED COMPOSITE FILMS FOR BRAIN-MACHINE INTERFACE APPLICATIONS (opens in a new tab)

  8. A Neural Signal Processor for Low-Latency Spike Inference

    … is a Field-Programmable Gate Array (FPGA)-based Neural Signal Processor (NSP) that receives raw input and generates labelled spikes as output, a process referred to as real-time spike inference. The second is a piece of software (Spiketag) that runs on a PC, communicates with the NSP, and …

    cambridge Repository record for A Neural Signal Processor for Low-Latency Spike Inference (opens in a new tab)