Wireless Power Transfer and Data Communication for Intracranial Neural Implants Case Study : Epilepsy Monitoring

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Adiabatic quantum-flux parametron (AQFP) is an energy-efficient superconducting technology. Before physical design can be performed, AQFP technology mapping involves not only mapping logic into supported gate types but also legalizing the circuit to fulfil ...

Implanted medical devices (IMDs) have been widely developed to support the monitoring and recording of biological data inside the body or brain. Wirelessly powered IMDs, a subset of implantable electronics, have been proposed to eliminate the limitations r ...

Proprioception tells the brain the state of the body based on distributed sensors in the body. However, the principles that govern proprioceptive processing from those distributed sensors are poorly understood. Here, we employ a task-driven neural network ...

A modular multiple frequency coils inductive link system to wirelessly provide power for at least a medical implant at an output of a receiving coil, whereby the receiving coil is configured to be implanted in an organism. The modular multiple frequency co ...

Recently, cutting-edge brain-machine interfaces (BMIs) have revealed the potential of decoders such as recurrent neural networks (RNNs) in predicting attempted handwriting [1] or speech [2], enabling rapid communication recovery after paralysis. However, c ...

This thesis presents an extensive exploration of neuroelectronic interfaces, focusing on microfabrication, in silico modeling, and their applications in designing and fabricating devices for neural interfacing. The research encompasses both peripheral nerv ...

In the development of implantable bioelectronics, the establishment of efficient wireless RF links between implants and external nodes is crucial, providing substantial contributions to the advancement of medical diagnosis, therapies, and basic science. Im ...

In two-stage solid-state transformers with input-series output-parallel structure, the LLC converter operating at a fixed switching frequency is a common choice for the isolated DC/DC conversion stage because it can provide a high efficiency and a fixed vo ...

Transformer models such as GPT generate human-like language and are predictive of human brain responses to language. Here, using functional-MRI-measured brain responses to 1,000 diverse sentences, we first show that a GPT-based encoding model can predict t ...

The medium-voltage (MV) dual active bridge (DAB) converter with series-connected SiC (S-SiC) MOSFETs is a promising solution for high-power-density isolated dc/dc converter. To improve the voltage sharing and reliability of S-SiC, relatively large snubber ...

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Solid-State Transformers with Input-Series/Output- Parallel configuration offer a convenient solution for AC/DC power conversion, thanks to their modularity, scalability and flexibility. However, as known, they are affected by a second-order harmonic rippl ...

Solid-State Transformers with Input-Series/Output-Parallel configuration offer a convenient solution for AC/DC conversion due to their scalability and modularity. In this configuration, each module experiences a second-order harmonic ripple caused by local ...

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

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-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

Wireless Power Transfer and Data Communication for Intracranial Neural Implants Case Study : Epilepsy Monitoring

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Technology Legalization and Optimization for Adiabatic Quantum-Flux Parametron

Integrated Wireless Power, Data Communication, and Thermal Sensing System for Autonomous Multisite Brain Implants

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

A modular multiple frequency inductive link to wirelessly power multiple miniaturized implants

33.3 MiBMI: A 192/512-Channel 2.46mm² Miniaturized Brain-Machine Interface Chipset Enabling 31-Class Brain-to-Text Conversion Through Distinctive Neural Codes

Modeling, fabrication and validation of 3D neural interfaces for peripheral nerves and brain organoids

Electromagnetic Radiation of Implantable Antennas

Ripple Voltage and Loss Reduction of Single-Phase ISOP SST by Eliminating the Second Harmonic Current in LLC Converters

Driving and suppressing the human language network using large language models

Phase Shift Angle Segmentation Modulation for Soft-Switching Medium-Voltage DAB Converter With Series-Connected SiC MOSFETs

Adversarial Training for Jamming-Robust Channel Estimation in OFDM Systems

Biophysically accurate and machine learning-based surrogate models to optimize neuroprosthesis design and operation

Predicting Visual Stimuli From Cortical Response Recorded With Wide-Field Imaging in a Mouse

Unraveling behavior and cortical signals to guide the development of soft neuroprostheses for auditory restoration and spreading depolarization

DC Power Distribution Networks with Direct Current Transformers

An Investigation of Manifold-Based Direct Control for a Brain-to-Body Neural Bypass

Stability Analysis of Second-Order Harmonic Active Filters for Input-Series/Output- Parallel Solid State Transformers

Stability Analysis of Input-Series/Output-Parallel Solid-State Transformers Equipped with Second-Order Harmonic Active Power Filters

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Deep Learning Theory Through the Lens of Diagonal Linear Networks