Realizing Low-Energy Classification Systems by Implementing Matrix Multiplication Directly Within an ADC
Realizing Low-Energy Classification Systems by Implementing Matrix Multiplication Directly Within an ADC
复制标题
通过直接在 ADC 内实现矩阵乘法来实现低能量分类系统
DOI：
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复制
发表时间：
2015
影响因子：
5.1
通讯作者：
N. Verma
中科院分区：
文献类型：
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作者：
Zhuo Wang;Jintao Zhang;N. Verma
在可穿戴和植入式医疗传感器应用中，低能量分类系统对于在设备内局部得出高质量的推断非常重要。考虑到传感器仪表通常会进行模数转换，本文提出了一种系统实现方式，其中分类所需的大部分计算都在ADC内实现。为了实现这一点，首先提出了一种算法配方，结合线性特征提取和分类到一个单一的矩阵变换。其次，提出了一种矩阵乘法ADC（MMADC），该ADC能够实现模拟输入样本与数字乘法器之间的乘法，除了A-D转换所需的能量之外，附加能量可以忽略不计。映射到MMADC的两个系统被证明：（1）基于ECG的心律失常检测器;和（2）基于图像像素的面部性别检测器。在所有执行的乘法上的RMS误差，标准化为理想乘法结果的RMS是0.018。此外，与传统系统的理想版本相比，所获得的能量节省估计分别为13倍和29倍，同时实现类似的性能水平。
In wearable and implantable medical-sensor applications, low-energy classification systems are of importance for deriving high-quality inferences locally within the device. Given that sensor instrumentation is typically followed by A-D conversion, this paper presents a system implementation wherein the majority of the computations required for classification are implemented within the ADC. To achieve this, first an algorithmic formulation is presented that combines linear feature extraction and classification into a single matrix transformation. Second, a matrix-multiplying ADC (MMADC) is presented that enables multiplication between an analog input sample and a digital multiplier, with negligible additional energy beyond that required for A-D conversion. Two systems mapped to the MMADC are demonstrated: (1) an ECG-based cardiac arrhythmia detector; and (2) an image-pixel-based facial gender detector. The RMS error over all multiplication performed, normalized to the RMS of ideal multiplication results is 0.018. Further, compared to idealized versions of conventional systems, the energy savings obtained are estimated to be 13× and 29×, respectively, while achieving similar level of performance.