Biomimetic Architectures for Sensing & Signal Processing

仿生传感架构

基本信息

批准号：
2323940
负责人：
金额：
--
依托单位：
University of Manchester
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2019
资助国家：
英国
起止时间：
2019 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2323940
关键词：
Biomimetic Architectures Sensing Signal Processing

项目摘要

The biological systems are capable of sensing, processing and communicating, information robustly with extremely low-power consumption, using hybrid neural network architectures constructed with slow, less accurate, highly heterogeneous neural elements, neurons and synapses. Most of this sensory and neural processing performed using spikes-based computations. Investigating and understanding these inherent spikes-based computational methods used in the sensors, sensory-pathways and cortex may help us to envisage and build future technologies that are energy-efficient and intelligent. Initially, the project investigates the spike-based sensing, communicating and processing principles by mimicking biological sensory and processing architectures in modern hardware technologies. Additionally, the student will also design and implement conventional biomedical architecture to sense and process a bio-signal to minimise noise and power consumption. Then, the student will investigate the ability to incorporate the bio-inspired techniques in sensors and signal processing architectures to realise low-power biomedical sensors and circuits that are less susceptible to noise and fault tolerance or robust to variability.The work carried out involve implementation of neuromorphic hardware cochleae, using a novel spike encoding algorithm and Gammatone filters, mimicking the operation of the biological cochlea. In parallel, the student will also develop fetal ECG signal capturing and signal processing architecture using conventional electronics. Then, the student will investigate and implement bio-inspired spikes-based techniques to detect ECG and fetal ECG signals.

使用混合神经网络体系结构以缓慢，准确，高度异质的神经元素，神经元和突触构建的混合神经网络体系结构，能够在极低的功率消耗中稳健地感测，处理和通信，以极低的功率消耗来感测，处理和通信。大多数使用基于峰值的计算进行的感觉和神经处理。调查和理解传感器，感觉轨道和皮层中使用的基于尖峰的固有计算方法可能有助于我们设想和构建能效和智能的未来技术。最初，该项目通过模仿现代硬件技术中的生物学感觉和处理体系结构来研究基于尖峰的感应，交流和处理原理。此外，学生还将设计和实施常规的生物医学体系结构，以感知和处理生物信号，以最大程度地减少噪声和功耗。然后，学生将调查将生物启发的技术纳入传感器和信号处理体系结构的能力生物耳蜗。同时，学生还将使用常规电子设备开发胎儿ECG信号捕获和信号处理结构。然后，学生将调查并实施以生物启发的基于峰值的技术来检测ECG和胎儿心电图信号。