Short Word-Length Entering Compressive Sensing Domain: Improved Energy Efficiency in Wireless Sensor Networks

This work combines compressive sensing and short word-length techniques to achieve localization and target tracking in wireless sensor networks with energy-efficient communication between the network anchors and the fusion center. Gradient descent localization is performed using time-of-arrival (TOA) data which are indicative of the distance between anchors and the target thereby achieving range-based localization. The short word-length techniques considered are delta modulation and sigma-delta modulation. The energy efficiency is due to the reduction of the data volume transmitted from anchors to the fusion center by employing any of the two delta modulation variants with compressive sensing techniques. Delta modulation allows the transmission of one bit per TOA sample. The communication energy efficiency is increased by RⱮ, R ≥ 1, where R is the sample reduction ratio of compressive sensing, and Ɱ is the number of bits originally present in a TOA-sample word. It is found that the localization system involving sigma-delta modulation has a superior performance to that using delta-modulation or pure compressive sampling alone, in terms of both energy efficiency and localization error in the presence of TOA measurement noise and transmission noise, owing to the noise shaping property of sigma-delta modulation.

Synchronization of Transmission Systems with ANS-DM Codecs

Adaptive Delta Modulation with Non-uniform Sampling (ANS-DM) is one of the waveform coding techniques, where a sampling instant and a quantization step size are adapted to the signal. The ANS-DM modulator produces an output binary stream, that carries information about the signal and includes necessary data of coder parameters (sampling instant and quantization step). In the demodulator, these values are recovered for proper signal reconstruction. The paper reports the problem of synchronizing clocks (transmitting and receiving) in the (ANS-DM) delta codecs systems. The original synchronization method, valuable in systems dedicated to the transmission of the bits with variable time duration was projected and experimentally verified. Performed measurements and observations have shown the elimination of the synchronization loss phenomenon.

Short Word-Length Entering Compressive Sensing Domain: Improved Energy-Efficiency in Wireless Sensor Networks

This work combines compressive sensing and short word-length techniques to achieve localization and target tracking in wireless sensor networks with energy-efficient communication between the network anchors and the fusion center. Gradient descent localization is performed using time-of-arrival (TOA) data which are indicative of the distance between anchors and the target thereby achieving range-based localization. The short word-length techniques considered are delta modulation and sigma-delta modulation. The energy efficiency is due to the reduction of the data volume transmitted from anchors to the fusion center by employing any of the two delta modulation variants with compressive sensing techniques. Delta modulation allows the transmission of one bit per TOA sample. The communication energy efficiency is increased by RⱮ, R≥1, where R is the sample reduction ratio of compressive sensing and Ɱ is the number of bits originally present in a TOA-sample word. It is found that the localization system involving sigma-delta modulation has a superior performance to that using delta-modulation or pure compressive sampling alone, in terms of both energy efficiency and localization error in the presence of TOA measurement noise, owing to the noise shaping property of sigma-delta modulation.

Delta band activity contributes to the identification of command following in disorder of consciousness

The overt or covert ability to follow commands in patients with disorders of consciousness is considered a sign of awareness and has recently been defined as cortically mediated behaviour. Despite its clinical relevance, the brain signatures of the perceptual processing supporting command following have been elusive. This multimodal study investigates the temporal spectral pattern of electrical brain activity to identify features that differentiated healthy controls from patients both able and unable to follow commands. We combined evidence from behavioural assessment, functional neuroimaging during mental imagery and high-density electroencephalography collected during auditory prediction, from 21 patients and 10 controls. We used a penalised regression model to identify command following using features from electroencephalography. We identified seven well-defined spatiotemporal signatures in the delta, theta and alpha bands that together contribute to identify DoC subjects with and without the ability to follow command, and further distinguished these groups of patients from controls. A fine-grained analysis of these seven signatures enabled us to determine that increased delta modulation at the frontal sensors was the main feature in command following patients. In contrast, higher frequency theta and alpha modulations differentiated controls from both groups of patients. Our findings highlight a key role of spatiotemporally specific delta modulation in supporting cortically mediated behaviour including the ability to follow command. However, patients able to follow commands nevertheless have marked differences in brain activity in comparison with healthy volunteers.

The ANSDM Converters Dynamic Range Design Process

The results of analytic and simulating works proved that for nonstationary sources, the delta converters with adaptive sampling expose higher coding efficiency than the former proposals, based on uniform sampling methods. The knowledge of the sampling interval range and the algorithm of the Nonuniform Sampling Delta Modulation and Adaptive Nonuniform Sampling Delta Modulation allows finding the necessary number of the sampling intervals and their values that maximizes SNR. The total dynamic range of the ANSDM modulator is the product of the dynamic range both from sampling interval and step size adaptation. Due to the high complexity of the calculations, the ANSDMsoft program was developed to support computing. All computational works were carried out using the Maple environment. Maple allows to solve complex mathematical functions and display their results in a simple way. Most importantly, it supports the LambertW function, used in the computing of NSDM or ANSDM modulators parameters. Graphic illustrations of the NSDM and ANSDM modulator dynamic range as a function of the minimum and maximum sampling frequency are presented.