This paper investigates the variability of various circuits and systems over temperature and presents several methods to improve their performance over temperature. The work demonstrates use of large scale reconfigurable System-On-Chip (SOC) for reducing the variability of circuits and systems compiled on a Floating Gate (FG) based Field Programmable Analog Array (FPAA). Temperature dependencies of circuits are modeled using an open-source simulator built in the Scilab/XCOS environment and the results are compared with measurement data obtained from the FPAA. This comparison gives further insight into the temperature dependence of various circuits and signal processing systems and allows us to compensate as well as predict their behavior. Also, the work presents several different current and voltage references that could help in reducing the variability caused due to changes in temperature. These references are standard blocks in the Scilab/Xcos environment that could be easily compiled on the FPAA. An FG based current reference is then used for biasing a 12 × 1 Vector Matrix Multiplication (VMM) circuit and a second order G m − C bandpass filter to demonstrate the compilation and usage of these voltage/current reference in a reconfigurable fabric. The large scale FG FPAA presented here is fabricated in a 350 nm CMOS process.Keywords: circuits and system; temperature dependence; reference generator; FPAA
Analog Processing and Temperature DependenceThe number of systems combining elements from within and among the emerging technologies of sensors, communications, and robotics grows every day. The computational abilities of these systems affect the overall system performance through various aspects (e.g., functionality, battery-life, foot-print, etc.). Traditionally most computational tasks have been performed in the digital domain, which can achieve high resolution computation at the cost of high power consumption [1]. For systems with a limited power budget, however, low-power, real-time computation techniques have been sought after. Accordingly, analog-signal-processing has been used extensively as an energy-efficient alternative to digital options [2][3][4].Recent mixed-mode large-scale Field-Programmable Analog Array (FPAA) enables advanced functionality for a wide spectrum of sensor applications [5]. These FPAAs combine the energy-efficiency, reconfigurability, and programmability of floating-gate-based analog signal processing with the precision and compatibility of digital, thereby a variety of analog circuitry implemented on FPAAs serve as building blocks of more complex signal processing functions [5].Many of the systems that can benefit from the computational power of an FPAA need to operate over a range of environments and temperatures. For instance, modern ubiquitous medical health assessment systems use physiologic signals collected from ambulatory subjects during daily outdoor