In this work, the relationship between Lyapunov exponents, used to estimate the effects of process variability, and the standard deviation obtained through the Monte Carlo method was established analytically, demonstrating that the Lyapunov exponents characterize a metric for estimating such effects. Based on this, a new metric for estimating the effects of process variability, based on Lyapunov exponents, was developed. The Sum-Power-Delay (SPD) was analytically defined, and its application was verified in the design of an inverter using 180nm technology. The SPD was applied to compare two sets of twenty cells designed in 180nm and 180nm-RH, a radiation-tolerant cell library developed at the Santa Maria Design House (SMDH), affiliated with the Federal University of Santa Maria (UFSM), demonstrating that circuits designed with Enclosed Layout-Transistor (ELT) are more robust against process variability. These results were obtained by analyzing circuits from the ISCAS85 benchmarks, as well as twenty circuits synthesized with our library. The same analysis was performed for matrix multiplication, aiming to evaluate the impact of process variability on this fundamental operation in space-grade digital systems. Finally, the 180nm-RH library was used to estimate the effects of process variability on circuits designed for space-oriented applications, including neural networks, filters, image compression, edge detection, and RISC-V microcontroller core modules. Key circuits for space applications, including image compressors, digital filters, and edge detection modules, were synthesized using a radiation-hardened standard cell library, enabling comparative evaluation of their robustness to process variability. The analysis provides valuable guidance for selecting circuits suitable for radiation-prone environments. Extension to RISC-V cores with 180 nm radiation-hardened transistors showed that Pico32 had the highest tolerance to process variability, confirming the practical effectiveness of the SPD metric in predicting and mitigating variability effects across designs.

The objective of this work is to unify, with mathematical rigor, the analyses to estimate the effects of process variability and the effects caused by radiation in digital circuits using a single analysis. First, we proved that to estimate the effects of process variability on delay and power, it is enough to estimate at least one of the two. Later, a relationship between the effects of radiation and the effects of variability was obtained through a common element between the two: the entropy of the circuit. We applied the presented methods to compare circuits with the operations: matrix multiplication, graph searches, encryption algorithms, and neural networks. All of the circuits are designed using a 180 nm technology. We were able to verify which circuits are more sensitive to the effects of variability and radiation simultaneously through the proposed method.

This article provides a comprehensive survey of pioneer and state-of-the-art localization algorithms based on the mobility of the network. The basic concepts of the localization task in a wireless sensor network are revisited and the most common techniques suitable for random mobility are reviewed. This survey compiles and discusses the most relevant algorithms regarding localization in mobile networks, focusing on scenarios where nodes have no control over their mobility and hardware restrictions are imposed, including recent advances in learning-based solutions. It focuses on presenting techniques that do not rely on human intervention or a specialized field configuration. This unpredictability brings challenges that are not present in a static network nor in a mobile network built upon robotic entities. The basis for theoretical concepts of localization algorithms is gathered and organized in a comprehensive way, so researchers may quickly get started in this field. Significant aspects addressed throughout the article, such as mobility pattern, range scheme, and computational complexity are organized and discussed as well as performance data for quantitative analysis alongside related ponderations. This survey concludes by pointing out current and future trends.

This paper presents the design and simulation results of a switched-current (SI) 2-2 MASH Sigma-Delta Modulator (ΣΔM). The modulator is composed by a low-distortion swing suppression topology which is highly suitable for wideband applications. It was realized using fully-differential circuitry with common-mode feedback. The circuit performs 14-bit dynamic range (DR) up to 5 MHz clock frequency and 20 kHz bandwidth. The modulator was designed in 0.6 μm CMOS technology and was sent to the foundry to prototype.

In the context of mobile sensor networks many challenges arise, position estimation being perhaps the most important. Localization is paramount for any application that requires interpretation of the data in a physical context. Collected data has no physical meaning if we are not able to determine the location of the samples of the phenomena under study. The two main sources of power consumption for nodes are the communication and local data processing. In this work we directly target the second one. We present the integrated implementation of a new localization algorithm for mobile wireless sensor networks based on the well-known range-free Centroid method. The proposed architecture splits the original sampling period of the Centroid algorithm into temporal windows in order to maintain a record of past information during movement, allowing for the weighing of the anchors' coordinates. We dramatically reduce energy consumption by implementing this concept into a dedicated circuit in a 0.13µm process. We achieved an order of magnitude in energy reduction, dissipating only 1.45mW and still maintain flexibility.