Tightening the uncertainty principle for stochastic currents

We connect two recent advances in the stochastic analysis of nonequilibrium systems: the (loose) uncertainty principle for the currents, which states that statistical errors are bounded by thermodynamic dissipation; and the analysis of thermodynamic consistency of the currents in the light of symmetries. Employing the large deviation techniques presented in [Gingrich et al., Phys. Rev. Lett. 2016] and [Pietzonka et al., Phys. Rev. E 2016], we provide a short proof of the loose uncertainty principle, and prove a tighter uncertainty relation for a class of thermodynamically consistent currents $J$. Our bound involves a measure of partial entropy production, that we interpret as the least amount of entropy that a system sustaining current $J$ can possibly produce, at a given steady state. We provide a complete mathematical discussion of quadratic bounds which allows to determine which are optimal, and finally we argue that the relationship for the Fano factor of the entropy production rate $\mathrm{var}\, \sigma / \mathrm{mean}\, \sigma \geq 2$ is the most significant realization of the loose bound. We base our analysis both on the formalism of diffusions, and of Markov jump processes in the light of Schnakenberg's cycle analysis.Comment: 13 pages, 4 figure

Real-Time Sensor Networks and Systems for the Industrial IoT: What Next?

The Industrial Internet of Things (Industrial IoT—IIoT) is the emerging core backbone construct for the various cyber-physical systems constituting one of the principal dimensions of the 4th Industrial Revolution [...

Fast switched current analog memory

In this paper is presented the structure of a fast Switched Current (SI) analog memory and its integration with a high energy nuclear physics experiment equipment. A special emphasis is focused on the structure of the elementary memory cell, the SI flash A/D converter, and the sampling commands generation. There can be found also a short comparation of the SI and SC techniques for analog memories

Algorithm validation and hardware design interactive approach

In this paper we will describe a modality to speed up the design of the VLSI digital (mainly DSP) circuits and to reduce the design errors by increasing the interaction between the ad-hoc software program developed to validate the algorithm and the VHDL description and simulation. A real case of a digital power analyzer will be used for exemplificatio

A high precision power supply meter

This paper describes an efficient implementation of a power supply meter. The implementation is based on the Fourier Series decomposition algorithm, using CORDIC algorithm for complex mathematical computations. It is able to calculate RMS and peak values, phase shift, power factor, and complex, active, and reactive power for two periodic waveforms up to the 25th harmonic. Several implementation alternatives are compared pointing out the advantages and the disadvantages of each one. Then the circuit structure at block level is described with emphasis on the advantages resulted from the use of CORDIC algorithm, followed by some considerations over precision issues

Design issues of a standard cell BiCMOS carrier transceiver on low voltage power lines

In this paper are described some of the issues of the mixed signal standard cell VLSI design with emphasis on the practical experience resulted from designing a carrier transceiver in SGS-THOMSON 2 μm BiCMOS technology. Presented are the circuit block structure, some advantages and disadvantages of the standard cell design approach, the testing strategy we implemented, and finally some practical conclusions resulting from our experience

Minteos mesh protocol and SystemC simulator

This paper presents our industrial experience on the implementation of Minteos Mesh Protocol which is a memory, power and delay efficient mesh protocol; and Minteos SystemC Simulator for mesh networks. Experiments are carried out to validate the adequate use of Minteos Mesh Protocol. Also, simulation/test results are given to show the effectiveness and applicability of Minteos SystemC simulator for mesh networks

Neural Networks for Indoor Person Tracking With Infrared Sensors

Indoor localization has many pervasive applications, like energy management, health monitoring, and security. Tagless localization detects directly the human body, like passive infrared sensing, and is the most amenable to different users and use cases. We evaluate the localization and tracking performance, as well as resource and processing requirements of various neural network (NN) types using directly the data from a low resolution 16-pixel thermopile sensor array in a 3 m x 3 m room. Out of the multilayer perceptron, autoregressive, 1D-CNN, and LSTM NN architectures that we test, the latter require more resources but can accurately locate and capture best the person movement dynamics, while the 1D-CNN provides the best compromise between localization accuracy (9.6 cm RMSE) and movement tracking smoothness with the least resources, and seem more suited for embedded applications

A BiCMOS current carrier transceiver on low voltage power lines

This paper presents a BiCMOS technology project of a Current Carrier Transceiver (CCT) for data and digital broadcasting on Low Voltage (LV) power lines (230-240~Vac). The CCT is the central piece in using the LV power lines network as communication channel for various "intelligent" sensors, actuators, monitors, and remote control for domotic or industrial purpose

Classifying visual field loss in glaucoma through baseline matching of stable reference sequences

Glaucoma is a common disease of the eye that often results in partial blindness. The main symptom of glaucoma is progressive loss of sight in the visual field over time. The clinical management of glaucoma involves monitoring the progress of the disease using a sequence of regular visual field tests. However, there is currently no universally accepted standard method for classifying changes in the visual field test data. Sequence matching techniques typically rely on similarity measures. However, visual field measurements are very noisy, particularly in people with glaucoma. It is therefore difficult to establish a reference data set including both stable and progressive visual fields. This paper proposes a method that uses a "baseline" computed from a query sequence, to match stable sequences in a database of visual field measurements collected from volunteers. The purpose of the new method is to classify a given query sequence as being stable or progressive. The results suggest that the new method gives a significant improvement in accuracy for identifying progressive sequences, though there is a small penalty for stable sequences