Farouk Vallette

High level modeling of signal integrity in field bus communication with SystemC-AMS

This paper presents a novel method for modeling the functionality of a mixed-signal system, and analyzing its signal integrity (SI) at a high-level of abstraction with SystemC-AMS. Our model includes on a unique platform a functional module and a non-functional module. The functional module represents the operative behavior of the system and the non-functional module, based on neural network techniques, displays the SI characteristics of the system. The proposed method is demonstrated by modeling field bus communication system with two nodes. We achieved an error of about 3% for the neural network based Time Data Flow (TDF) model with respect to a RLC Electrical Linear Networks (ELN) model.

A self-sufficient digitally controlled ring oscillator compensated for supply voltage variation

A self-sufficient Giga-Hertz digitally controlled ring oscillator for clock distribution network is presented in this paper. It features a high supply insensitivity in order to mitigate the additional jitter due to supply noise. This is achieved by inducing a mutual compensation between the oscillation frequency parameters that are affected by the supply voltage variations. The proposed method can be easily implemented and takes advantage of the deep sub-micrometer effects peculiar to topical CMOS technologies. We demonstrate by simulations that this approach remains efficient over process variations despite the reliability issue of short channel MOS transistors.

High-Level Virtual Prototyping of Signal Integrity in Bus Communication

In this paper, a novel methodology for high-level modeling of bus communication in embedded systems is introduced. It allows the dynamic evaluation of their signal integrity (SI) characteristics at the virtual prototyping step (i.e., before physical realization). The method is based on the association of functional and nonfunctional modules. Functional modules represent the ideal behavior of the system, while nonfunctional modules use neural networks to model SI effects. This approach was implemented in SystemC-AMS, using the timed data flow model of computation. The method is illustrated by a Universal Serial Bus (USB) 3.0 application, where modular and parameterizable models are introduced. The method achieved good accuracy (<;5%) while allowing significant simulation speedup (up to 2000 times), compared with SPICE-based reference models. This methodology can be used to perform an early SI analysis in the virtual prototyping of bus communication in the embedded systems.

In vivo NIRS monitoring in pig Spinal Cord tissues

Little is known about the processes occurring after Spinal Cord damage. Whether permanent or recoverable, those processes have not been precisely characterized because their mechanism is complex and information on the functioning of this organ are partial. This study demonstrates the feasibility of Spinal Cord activity monitoring using Near Infra-Red Spectroscopy in a pig animal model. This animal has been chosen because of its comparable size and its similarities with humans. In the first step, optical characterization of the Spinal Cord tissues was performed in different conditions using a spectrophotometer. Optical Density was evaluated between 3.5 and 6.5 in the [500; 950] nm range. Secondly, adapted light sources with custom probes were used to observe autonomic functions in the spine. Results on the measured haemodynamics at rest and under stimulation show in real time the impact of a global stimulus on a local section of the Spinal Cord. The photoplethysmogram signal of the Spinal Cord showed low AC-to-DC ratio (below to 1 %).