To provide multiple options for specific application in biosignal processing, the programmable Gaussian-derived Gm-C wavelet filter has been proposed. To realize the programmable characteristic, the analog wavelet base with one numerator term is constructed by using hybrid artificial fish swarm algorithm. Also, the inverse follow-the-leader feedback Gm-C filter structure with a switch array is employed. By programming switches only, Gaussian and Marr wavelet transforms can be realized flexibly with all component parameters unchanged. The seventh-order programmable wavelet filter is designed as an example. Simulation results show that power consumption is only 141.68 pW at scale a = 0.1, with dynamic range of 42.6 dB and figure-of-merit of 2.05 × 10⁻¹³. Due to the programmability, the proposed design method can implement two wavelet filters with very low circuit complexity.

中文翻译：

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可穿戴生物医学传感器可编程高斯小波滤波器的设计

为了为生物信号处理中的特定应用提供多种选择，提出了可编程的高斯导出 Gm-C 小波滤波器。为实现可编程特性，采用混合人工鱼群算法构建了一个分子项的模拟小波基。此外，还采用了具有开关阵列的逆跟随领先反馈 Gm-C 滤波器结构。只需对开关进行编程，就可以灵活地实现高斯和马尔小波变换，且所有元件参数不变。以七阶可编程小波滤波器为例进行设计。仿真结果表明，在标度a  = 0.1 时功耗仅为 141.68 pW ，动态范围为 42.6 dB，品质因数为 2.05 × 10 ^-13. 由于可编程性，所提出的设计方法可以以非常低的电路复杂度实现两个小波滤波器。