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相关概念视频

Discrete Fourier Transform01:15

Discrete Fourier Transform

209
The Discrete Fourier Transform (DFT) is a fundamental tool in signal processing, extending the discrete-time Fourier transform by evaluating discrete signals at uniformly spaced frequency intervals. This transformation converts a finite sequence of time-domain samples into frequency components, each representing complex sinusoids ordered by frequency. The DFT translates these sequences into the frequency domain, effectively indicating the magnitude and phase of each frequency component present...
209
Discrete-time Fourier transform01:26

Discrete-time Fourier transform

252
The Discrete-Time Fourier Transform (DTFT) is an essential mathematical tool for analyzing discrete-time signals, converting them from the time domain to the frequency domain. This transformation allows for examining the frequency components of discrete signals, providing insights into their spectral characteristics. In the DTFT, the continuous integral used in the continuous-time Fourier transform is replaced by a summation to accommodate the discrete nature of the signal.
One of the notable...
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相关实验视频

Updated: May 26, 2025

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
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基于阵列的超低功率离散里埃变换,用于闭环神经传感.

Richard Yang1, Heather D Orser2, Kip A Ludwig3

  • 1Department of Biomedical Engineering, the Department of Computer Science, and the Wisconsin Institute for Translational Neuroengineering, University of Wisconsin-Madison, Madison WI 53701 USA.

bioRxiv : the preprint server for biology
|February 24, 2025
PubMed
概括

一个新的最小架构的单延迟反离散里埃变换 (mSDF-DFT) 为植入式医疗设备提供了显著的节能. 这种超低功耗方法在神经传感应用中将动态功率降低33%.

关键词:
深度大脑刺激 刺激大脑金融金融公司 (FFT)在FPGA中,FPGA是指FPGA.富里叶变换是什么意思?可植入的脉冲发生器医疗设备 医疗设备神经技术的神经技术实时信号处理 实时信号处理

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Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
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相关实验视频

Last Updated: May 26, 2025

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Published on: March 25, 2014

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Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments
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科学领域:

  • 生物医学工程 生物医学工程
  • 信号处理 信号处理
  • 数字系统 数字系统

背景情况:

  • 离散里埃变换 (DFT) 的数字实现对于分析生物潜力和量化神经疾病生物标志物对于自适应性深度大脑刺激至关重要.
  • 快速里埃转换 (FFT) 算法消耗大量电力,在资源有限的环境中对电池驱动的植入式医疗设备构成挑战.

研究的目的:

  • 引入适用于资源有限的嵌入式应用程序的超低功率里叶转换方法.
  • 为了呈现一个最小的架构,单延迟反离散的福里埃转换 (mSDF-DFT),优先考虑逻辑复杂性降低,以提高能源效率.

主要方法:

  • 开发一种新的最小架构,单延迟反离散里埃变换 (mSDF-DFT).
  • 对于超低功率场可编程门阵列应用的msdf-dft架构的评估.
  • 能源和电力消耗与最先进的FFT方法的比较.

主要成果:

  • 与最先进的FFT算法相比,mSDF-DFT实现了动态功率的33%降低.
  • 在使用mSDF-DFT的神经传感应用中,资源利用率降低了4%.
  • 在超低功率场景中显示出显著的能量和功率改进.

结论:

  • mSDF-DFT为生物潜能分析的传统FT方法提供了一种可行的超低功耗替代方案.
  • 该架构对于闭环深度大脑刺激和其他可植入的医疗设备特别有益.
  • mSDF-DFT可以轻松扩展到医疗设备以外的各种超低功耗嵌入式应用.