Single-Event Upset Analysis and Protection in High Speed Circuits

The effect of single-event transients (SETs) (at a combinational node of a design) on the system reliability is becoming a big concern for ICs manufactured using advanced technologies. An SET at a node of combinational part may cause a transient pulse at the input of a flip-flop and consequently is latched in the flip-flop and generates a soft-error. When an SET conjoined with a transition at a node along a critical path of the combinational part of a design, a transient delay fault may occur at the input of a flip-flop. On the other hand, increasing pipeline depth and using low power techniques such as multi-level power supply, and multi-threshold transistor convert almost all paths in a circuit to critical ones. Thus, studying the behavior of the SET in these kinds of circuits needs special attention. This paper studies the dynamic behavior of a circuit with massive critical paths in the presence of an SET. We also propose a novel flip-flop architecture to mitigate the effects of such SETs in combinational circuits. Furthermore, the proposed architecture can tolerant a single event upset (SEU) caused by particle strike on the internal nodes of a flip-flo

Two-photon imaging and analysis of neural network dynamics

The glow of a starry night sky, the smell of a freshly brewed cup of coffee or the sound of ocean waves breaking on the beach are representations of the physical world that have been created by the dynamic interactions of thousands of neurons in our brains. How the brain mediates perceptions, creates thoughts, stores memories and initiates actions remains one of the most profound puzzles in biology, if not all of science. A key to a mechanistic understanding of how the nervous system works is the ability to analyze the dynamics of neuronal networks in the living organism in the context of sensory stimulation and behaviour. Dynamic brain properties have been fairly well characterized on the microscopic level of individual neurons and on the macroscopic level of whole brain areas largely with the help of various electrophysiological techniques. However, our understanding of the mesoscopic level comprising local populations of hundreds to thousands of neurons (so called 'microcircuits') remains comparably poor. In large parts, this has been due to the technical difficulties involved in recording from large networks of neurons with single-cell spatial resolution and near- millisecond temporal resolution in the brain of living animals. In recent years, two-photon microscopy has emerged as a technique which meets many of these requirements and thus has become the method of choice for the interrogation of local neural circuits. Here, we review the state-of-research in the field of two-photon imaging of neuronal populations, covering the topics of microscope technology, suitable fluorescent indicator dyes, staining techniques, and in particular analysis techniques for extracting relevant information from the fluorescence data. We expect that functional analysis of neural networks using two-photon imaging will help to decipher fundamental operational principles of neural microcircuits.Comment: 36 pages, 4 figures, accepted for publication in Reports on Progress in Physic

Accurate Settling-Time Modeling and Design Procedures for Two-Stage Miller-Compensated Amplifiers for Switched-Capacitor Circuits

We present modeling techniques for accurate estimation of settling errors in switched-capacitor (SC) circuits built with Miller-compensated operational transconductance amplifiers (OTAs). One distinctive feature of the proposal is the computation of the impact of signal levels (on both the model parameters and the model structure) as they change during transient evolution. This is achieved by using an event-driven behavioral approach that combines small- and large-signal behavioral descriptions and keeps track of the amplifier state after each clock phase. Also, SC circuits are modeled under closed-loop conditions to guarantee that the results remain close to those obtained by electrical simulation of the actual circuits. Based on these models, which can be regarded as intermediate between the more established small-signal approach and full-fledged simulations, design procedures for dimensioning SC building blocks are presented whose targets are system-level specifications (such as ENOB and SNDR) instead of OTA specifications. The proposed techniques allow to complete top-down model-based designs with 0.3-b accuracy.Ministerio de Educación y Ciencia TEC2006-03022Junta de Andalucía TIC-0281

Variable domain transformation for linear PAC analysis of mixed-signal systems

This paper describes a method to perform linear AC analysis on mixed-signal systems which appear strongly nonlinear in the voltage domain but are linear in other variable domains. Common circuits like phase/delay-locked loops and duty-cycle correctors fall into this category, since they are designed to be linear with respect to phases, delays, and duty-cycles of the input and output clocks, respectively. The method uses variable domain translators to change the variables to which the AC perturbation is applied and from which the AC response is measured. By utilizing the efficient periodic AC (PAC) analysis available in commercial RF simulators, the circuit’s linear transfer function in the desired variable domain can be characterized without relying on extensive transient simulations. Furthermore, the variable domain translators enable the circuits to be macromodeled as weakly-nonlinear systems in the chosen domain and then converted to voltage-domain models, instead of being modeled as strongly-nonlinear systems directly

System thermal-hydraulic modelling of the phénix dissymmetric test benchmark

Phénix is a French pool-type sodium-cooled prototype reactor; before the definitive shutdown, occurred in 2009, a final set of experimental tests are carried out in order to increase the knowledge on the operation and the safety aspect of the pool-type liquid metal-cooled reactors. One of the experiments was the Dissymmetric End-of-Life Test which was selected for the validation benchmark activity in the frame of SESAME project. The computer code validation plays a key role in the safety assessment of the innovative nuclear reactors and the Phénix dissymmetric test provides useful experimental data to verify the computer codes capability in the asymmetric thermal-hydraulic behaviour into a pool-type liquid metal-cooled reactor. This paper shows the comparison of the outcomes obtained with six different System Thermal-Hydraulic (STH) codes: RELAP5-3D©, SPECTRA, ATHLET, SAS4A/SASSYS-1, ASTEC-Na and CATHARE. The nodalization scheme of the reactor was individually achieved by the participants; during the development of the thermal-hydraulic model, the pool nodalization methodology had a special attention in order to investigate the capability of the STH codes to reproduce the dissymmetric effects which occur in each loop and into pools, caused by the azimuthal asymmetry of the boundary conditions. The modelling methodology of the participants is discussed and the main results are compared in this paper to obtain useful guide lines for the future modelling of innovative liquid metal pool-type reactors

A sub-mW IoT-endnode for always-on visual monitoring and smart triggering

This work presents a fully-programmable Internet of Things (IoT) visual sensing node that targets sub-mW power consumption in always-on monitoring scenarios. The system features a spatial-contrast $128\mathrm{x}64$ binary pixel imager with focal-plane processing. The sensor, when working at its lowest power mode ($10\mu W$ at 10 fps), provides as output the number of changed pixels. Based on this information, a dedicated camera interface, implemented on a low-power FPGA, wakes up an ultra-low-power parallel processing unit to extract context-aware visual information. We evaluate the smart sensor on three always-on visual triggering application scenarios. Triggering accuracy comparable to RGB image sensors is achieved at nominal lighting conditions, while consuming an average power between $193\mu W$ and $277\mu W$, depending on context activity. The digital sub-system is extremely flexible, thanks to a fully-programmable digital signal processing engine, but still achieves 19x lower power consumption compared to MCU-based cameras with significantly lower on-board computing capabilities.Comment: 11 pages, 9 figures, submitteted to IEEE IoT Journa