Commissariat &#xc0; L'&#xc9;nergie Atomique Et Aux &#xc9;nergies Alternatives

Commissariat a L'energie Atomique

Schneider Electric Industries Sas

Rodolphe Heliot

Romain Wacquez

Marc Belleville

Dominique David

Marc Duranton

Sigrid Thomas

Xavier Jehl

Christine Azevedo-Coste

Bernard Espiau

Benoit Vinot

Nicolas Gast

Florent Cadoux

Marc Sanquer

Antoine Joubert

Roger Pissard-Gibollet

Benoît Vinot

A method for monitoring and controlling an electrical network that includes at least one transformer station delimiting a medium-voltage sub-network and a low-voltage sub-network and a plurality of entities that are connected to a determined voltage in the low-voltage sub-network, each entity being a consumer and/or a producer of electricity in the low-voltage sub-network. The method includes determining control data on the production and/or on the consumption of electricity to be applied to one or more entities of the low-voltage sub-network taking into account previously determined production and/or consumption quotas.

Method for monitoring and controlling an electrical network

Neuromorphic circuits are multi-cell networks configured to imitate the behavior of biological neural networks. A neuromorphic circuit is provided which comprises a network of neurons each identified by a neuron address in the network, each neuron being able to receive and process at least one input signal and then later emit on an output of the neuron a signal representing an event which occurs inside the neuron, and a programmable memory composed of elementary memories each associated with a respective neuron. The elementary memory, which is a memory of post-synaptic addresses and weights, comprises an activation input linked by a conductor to the output of the associated neuron to directly receive an event signal emitted by this neuron without passing through an address encoder or decoder. The post-synaptic addresses extracted from an elementary memory activated by a neuron are applied, with associated synaptic weights, as inputs to the neural network.

Electronic circuit with neuromorphic architecture

A digital-to-analogue converter, with application to electronic circuits with neuromorphic architecture, comprises: transistors of identical nominal geometrical characteristics, but of dispersed current-voltage characteristics, wherein when a constant gate-source voltage is applied to the different transistors, a current varying as a function of the dispersion circulates in the transistor; a digital table receiving a digital word and having a selection output selecting, as a function of the word to be converted, a transistor or transistors supplying a current of desired value representing this word in analogue form. The look-up table is loaded as a function of real measured current-voltage characteristics of different transistors of the set, to establish a look-up between words and current values. The wide variability of characteristics of the transistors, notably their leakage current for a gate-source voltage below the switch-on threshold, allows finding combinations of leakage currents which are a good representation of words to be converted.

Digital-to-analogue converter and neuromorphic circuit using such a converter

A neuromorphic data processing device comprising a plurality of spiking neurons, with each of these neurons comprising: an integrator designed to receive successive analog pulses each having a certain value, and accumulate the values of the pulses received in a recorded value, referred to as accumulation value, and a discharger designed to emit a pulse, referred to as discharge pulse, according to the accumulation value, and a silicon support having two surfaces, the neurons being carried out on at least one of the two surfaces, the integrator of each neuron comprising a metal via of the TSV type between the two surfaces of the silicon support, the metal via of the TSV type forming a capacitor with the silicon support and having an electric potential forming the accumulation value wherein the values of the pulses received are accumulated and according to which the discharge pulse is emitted.

Device and method for neuromorphic data processing using spiking neurons

The process comprises acquisition of experimental data from measurements of physical quantities by means of at least one sensor associated to the object. The process comprises a first reliable estimation of a first range of values with a first method. The process comprises at least one additional estimation of an additional range of values with a different method. The methods each present a predetermined reliability. The ranges of values are successively observed in order of decreasing reliability of the corresponding methods. Each additional range of values is compared with the range of values corresponding to the previous method according to said order. The additional range is chosen as result when the additional range is comprised in the range corresponding to one of the previous methods.

Process for estimating the motion phase of an object

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Grenoble, France

Rodolphe Heliot