A Design Methodology for Space-Time Adapter

This paper presents a solution to efficiently explore the design space of communication adapters. In most digital signal processing (DSP) applications, the overall architecture of the system is significantly affected by communication architecture, so the designers need specifically optimized adapters. By explicitly modeling these communications within an effective graph-theoretic model and analysis framework, we automatically generate an optimized architecture, named Space-Time AdapteR (STAR). Our design flow inputs a C description of Input/Output data scheduling, and user requirements (throughput, latency, parallelism...), and formalizes communication constraints through a Resource Constraints Graph (RCG). The RCG properties enable an efficient architecture space exploration in order to synthesize a STAR component. The proposed approach has been tested to design an industrial data mixing block example: an Ultra-Wideband interleaver.Comment: ISBN : 978-1-59593-606-

Statistical Power Supply Dynamic Noise Prediction in Hierarchical Power Grid and Package Networks

One of the most crucial high performance systems-on-chip design challenge is to front their power supply noise sufferance due to high frequencies, huge number of functional blocks and technology scaling down. Marking a difference from traditional post physical-design static voltage drop analysis, /a priori dynamic voltage drop/evaluation is the focus of this work. It takes into account transient currents and on-chip and package /RLC/ parasitics while exploring the power grid design solution space: Design countermeasures can be thus early defined and long post physical-design verification cycles can be shortened. As shown by an extensive set of results, a carefully extracted and modular grid library assures realistic evaluation of parasitics impact on noise and facilitates the power network construction; furthermore statistical analysis guarantees a correct current envelope evaluation and Spice simulations endorse reliable result

Backwards is the way forward: feedback in the cortical hierarchy predicts the expected future

Clark offers a powerful description of the brain as a prediction machine, which offers progress on two distinct levels. First, on an abstract conceptual level, it provides a unifying framework for perception, action, and cognition (including subdivisions such as attention, expectation, and imagination). Second, hierarchical prediction offers progress on a concrete descriptive level for testing and constraining conceptual elements and mechanisms of predictive coding models (estimation of predictions, prediction errors, and internal models)

Transcranial magnetic stimulation disrupts the perception and embodiment of facial expressions

Copyright © 2008 Society for Neuroscience and the authors. The The Journal of Neuroscience uses a Creative Commons Attribution-NonCommercial-ShareAlike licence: http://creativecommons.org/licenses/by-nc-sa/4.0/.Theories of embodied cognition propose that recognizing facial expressions requires visual processing followed by simulation of the somatovisceral responses associated with the perceived expression. To test this proposal, we targeted the right occipital face area (rOFA) and the face region of right somatosensory cortex (rSC) with repetitive transcranial magnetic stimulation (rTMS) while participants discriminated facial expressions. rTMS selectively impaired discrimination of facial expressions at both sites but had no effect on a matched face identity task. Site specificity within the rSC was demonstrated by targeting rTMS at the face and finger regions while participants performed the expression discrimination task. rTMS targeted at the face region impaired task performance relative to rTMS targeted at the finger region. To establish the temporal course of visual and somatosensory contributions to expression processing, double-pulse TMS was delivered at different times to rOFA and rSC during expression discrimination. Accuracy dropped when pulses were delivered at 60–100 ms at rOFA and at 100–140 and 130–170 ms at rSC. These sequential impairments at rOFA and rSC support embodied accounts of expression recognition as well as hierarchical models of face processing. The results also demonstrate that nonvisual cortical areas contribute during early stages of expression processing.Biotechnology and Biological Sciences Research Counci