Energy integration describes sound-intensity coding in an insect auditory system

We investigate the transduction of sound stimuli into neural responses and focus on locust auditory receptor cells. As in other mechanosensory model systems, these neurons integrate acoustic inputs over a fairly broad frequency range. To test three alternative hypotheses about the nature of this spectral integration (amplitude, energy, pressure), we perform intracellular recordings while stimulating with superpositions of pure tones. On the basis of online data analysis and automatic feedback to the stimulus generator, we systematically explore regions in stimulus space that lead to the same level of neural activity. Focusing on such iso-firing-rate regions allows for a rigorous quantitative comparison of the electrophysiological data with predictions from the three hypotheses that is independent of nonlinearities induced by the spike dynamics. We find that the dependence of the firing rates of the receptors on the composition of the frequency spectrum can be well described by an energy-integrator model. This result holds at stimulus onset as well as for the steady-state response, including the case in which adaptation effects depend on the stimulus spectrum. Predictions of the model for the responses to bandpass-filtered noise stimuli are verified accurately. Together, our data suggest that the sound-intensity coding of the receptors can be understood as a three-step process, composed of a linear filter, a summation of the energy contributions in the frequency domain, and a firing-rate encoding of the resulting effective sound intensity. These findings set quantitative constraints for future biophysical models

Pre-integration lateral inhibition enhances unsupervised learning

A large and influential class of neural network architectures use post-integration lateral inhibition as a mechanism for competition. We argue that these algorithms are computationally deficient in that they fail to generate, or learn, appropriate perceptual representations under certain circumstances. An alternative neural network architecture is presented in which nodes compete for the right to receive inputs rather than for the right to generate outputs. This form of competition, implemented through pre-integration lateral inhibition, does provide appropriate coding properties and can be used to efficiently learn such representations. Furthermore, this architecture is consistent with both neuro-anatomical and neuro-physiological data. We thus argue that pre-integration lateral inhibition has computational advantages over conventional neural network architectures while remaining equally biologically plausible

Motion estimation and CABAC VLSI co-processors for real-time high-quality H.264/AVC video coding

Real-time and high-quality video coding is gaining a wide interest in the research and industrial community for different applications. H.264/AVC, a recent standard for high performance video coding, can be successfully exploited in several scenarios including digital video broadcasting, high-definition TV and DVD-based systems, which require to sustain up to tens of Mbits/s. To that purpose this paper proposes optimized architectures for H.264/AVC most critical tasks, Motion estimation and context adaptive binary arithmetic coding. Post synthesis results on sub-micron CMOS standard-cells technologies show that the proposed architectures can actually process in real-time 720 × 480 video sequences at 30 frames/s and grant more than 50 Mbits/s. The achieved circuit complexity and power consumption budgets are suitable for their integration in complex VLSI multimedia systems based either on AHB bus centric on-chip communication system or on novel Network-on-Chip (NoC) infrastructures for MPSoC (Multi-Processor System on Chip

eCMT-SCTP: Improving Performance of Multipath SCTP with Erasure Coding Over Lossy Links

Performance of transport protocols on lossy links is a well-researched topic, however there are only a few proposals making use of the opportunities of erasure coding within the multipath transport protocol context. In this paper, we investigate performance improvements of multipath CMT-SCTP with the novel integration of the on-the-fly erasure code within congestion control and reliability mechanisms. Our contributions include: integration of transport protocol and erasure codes with regards to congestion control; proposal for a variable retransmission delay parameter (aRTX) adjustment; performance evaluation of CMT-SCTP with erasure coding with simulations. We have implemented the explicit congestion notification (ECN) and erasure coding schemes in NS-2, evaluated and demonstrated results of improvement both for application goodput and decline of spurious retransmission. Our results show that we can achieve from 10% to 80% improvements in goodput under lossy network conditions without a significant penalty and minimal overhead due to the encoding-decoding process

Interactivity within IMS Learning Design and Question and Test Interoperability

We examine the integration of IMS Question and Test Interoperability (QTI) and IMS Learning Design (LD) in implementations of E-learning from both pedagogical and technological points of view. We propose the use of interactivity as a parameter to evaluate the quality of assessment and E-learning, and assess various cases of individual and group study for their interactivity, ease of coding, flexibility, and reusability. We conclude that presenting assessments using IMS QTI provides flexibility and reusability within an IMS LD Unit Of Learning (UOL) for individual study. For group study, however, the use of QTI items may involve coding difficulties if group members need to wait for their feedback until all students have attempted a question, and QTI items may not be able to be used at all if the QTI services are implemented within a service-oriented architecture