A Low-Power Analog Processor-in-Memory-Based Convolutional Neural Network for Biosensor Applications.

This paper presents an on-chip implementation of an analog processor-in-memory (PIM)-based convolutional neural network (CNN) in a biosensor. The operator was designed with low power to implement CNN as an on-chip device on the biosensor, which consists of plates of 32 × 32 material. In this paper, 10T SRAM-based analog PIM, which performs multiple and average (MAV) operations with multiplication and accumulation (MAC), is used as a filter to implement CNN at low power. PIM proceeds with MAV operations, with feature extraction as a filter, using an analog method. To prepare the input feature, an input matrix is formed by scanning a 32 × 32 biosensor based on a digital controller operating at 32 MHz frequency. Memory reuse techniques were applied to the analog SRAM filter, which is the core of low power implementation, and in order to accurately grasp the MAC operational efficiency and classification, we modeled and trained numerous input features based on biosignal data, confirming the classification. When the learned weight data was input, 19 mW of power was consumed during analog-based MAC operation. The implementation showed an energy efficiency of 5.38 TOPS/W and was differentiated through the implementation of 8 bits of high resolution in the 180 nm CMOS process.

A Configurable and Fully Synthesizable RTL-Based Convolutional Neural Network for Biosensor Applications.

This paper presents a register-transistor level (RTL) based convolutional neural network (CNN) for biosensor applications. Biosensor-based diseases detection by DNA identification using biosensors is currently needed. We proposed a synthesizable RTL-based CNN architecture for this purpose. The adopted technique of parallel computation of multiplication and accumulation (MAC) approach optimizes the hardware overhead by significantly reducing the arithmetic calculation and achieves instant results. While multiplier bank sharing throughout the convolutional operation with fully connected operation significantly reduces the implementation area. The CNN model is trained in MATLAB® on MNIST® handwritten dataset. For validation, the image pixel array from MNIST® handwritten dataset is applied on proposed RTL-based CNN architecture for biosensor applications in ModelSim®. The consistency is checked with multiple test samples and 92% accuracy is achieved. The proposed idea is implemented in 28 nm CMOS technology. It occupies 9.986 mm2 of the total area. The power requirement is 2.93 W from 1.8 V supply. The total time taken is 8.6538 ms.

A 0.617-2.7 GHz Highly Linear High-Power Dual Port 15 Throws Antenna Switch Module (DP15T-ASM) with Branched-Antenna Technique and Termination Mode.

This paper presents a Dual-Port-15-Throw (DP15T) antenna switch module (ASM) Radio Frequency (RF) switch implemented by a branched antenna technique which has a high linearity for wireless communications and various frequency bands, including a low- frequency band of 617-960 MHz, a mid-frequency band of 1.4-2.2 GHz, and a high-frequency band of 2.3-2.7 GHz. To obtain an acceptable Insertion Loss (IL) and provide a consistent input for each throw, a branched antenna technique is proposed that distributes a unified magnetic field at the inputs of the throws. The other role of the proposed antenna is to increase the inductance effects for the closer ports to the antenna pad in order to decrease IL at higher frequencies. The module is enhanced by two termination modes for each antenna path to terminate the antenna when the switch is not operating. The module is fabricated in the silicon-on-insulator CMOS process. The measurement results show a maximum IMD2 and IMD3 of -100 dBm, while for the second and third harmonics the maximum value is -89 dBc. The module operates with a maximum power handling of 35 dBm. Experimental results show a maximum IL of 0.34 and 0.92 dB and a minimum isolation of 49 dB and 35.5 dB at 0.617 GHz and 2.7 GHz frequencies, respectively. The module is implemented in a compact way to occupy an area of 0.74 mm2. The termination modes show a second harmonic of 75 dBc, which is desirable.