公开(公告)号：US20230131067A1

公开(公告)日：2023-04-27

申请号：US17968163

申请日：2022-10-18

Applicant: STMicroelectronics (Rousset) SAS

Inventor： Pierre Demaj ,  Laurent Folliot

IPC: G06N3/02 ,  G06K9/00

Abstract: According to one aspect, a method is proposed for detecting events or elements in physical signals by implementing an artificial neural network. The method includes an assessment of a probability of the presence of the event or the element by an implementation of the neural network. The implementation of the neural network according to a nominal mode takes as input a physical signal having a first resolution, called nominal resolution, when the probability of presence of the event or the element is greater than a threshold. The implementation of the neural network according to a low power mode takes as input a physical signal having a second resolution, called reduced resolution, lower than the first resolution, when the probability of presence of the event or the element is below the threshold.

公开(公告)号：US11354238B2

公开(公告)日：2022-06-07

申请号：US16691957

申请日：2019-11-22

Applicant: STMicroelectronics (Rousset) SAS

Inventor： Laurent Folliot ,  Pierre Demaj

IPC: G06N3/04 ,  G06F12/02 ,  G06F12/06

Abstract: A method can be used to determine an overall memory size of a global memory area to be allocated in a memory intended to store input data and output data from each layer of a neural network. An elementary memory size of an elementary memory area intended to store the input data and the output data from the layer is determined for each layer. The elementary memory size is in the range between a memory size for the input data or output data from the layer and a size equal to the sum of the memory size for the input data and the memory size for the output data from the layer. The overall memory size is determined based on the elementary memory sizes associated with the layers. The global memory area contains all the elementary memory areas.

公开(公告)号：US10863018B2

公开(公告)日：2020-12-08

申请号：US16774954

申请日：2020-01-28

Applicant: STMicroelectronics (Rousset) SAS

Inventor： Pierre Demaj ,  Laurent Folliot

IPC: H04M1/725 ,  G01D21/02 ,  H04W4/02 ,  H04W12/00 ,  H04W4/029 ,  H04W52/02 ,  G06F9/445 ,  G06F3/01 ,  G06K9/00 ,  H04W4/38 ,  H04W56/00 ,  H04W4/33 ,  H04W4/23

Abstract: A method of real-time scene detection performed by a wireless communication device includes, performing a first scene detection measurement to determine that the wireless communication device is located in a first scene. The first scene detection measurement is performed at first instant in time. The first scene is a type of environment. The method further includes associating the first scene with a corresponding reference scene of a predetermined set of reference scenes, determining a reference duration associated with the corresponding reference scene, and performing a second scene detection measurement immediately following expiration of the reference duration measured from the first instant in time.

公开(公告)号：US20200302266A1

公开(公告)日：2020-09-24

申请号：US16810582

申请日：2020-03-05

Applicant: STMicroelectronics (Rousset) SAS

Inventor： Pierre Demaj ,  Laurent Folliot

IPC: G06N3/04

Abstract: In accordance with an embodiment, a method includes reducing a size of at least one initial parameter of each layer of an initial multilayer neural network to obtain for each layer a set of new parameters defining a new neural network, wherein each new parameter of the set of new parameters has its data represented in two portions comprising an integer portion and a fractional portion; implementing the new neural network using a test input data set applied only once to each layer; determining a distribution function or a density function resulting from the set of new parameters for each layer; and based on the determined distribution function or density function, adjusting a size of a memory area allocated to the fractional portion and a size of the memory area allocated to the integer portion of each new parameter associated with each layer.

公开(公告)号：US20200183834A1

公开(公告)日：2020-06-11

申请号：US16691957

申请日：2019-11-22

Applicant: STMicroelectronics (Rousset) SAS

Inventor： Laurent Folliot ,  Pierre Demaj

IPC: G06F12/06 ,  G06N3/04

Abstract: A method can be used to determine an overall memory size of a global memory area to be allocated in a memory intended to store input data and output data from each layer of a neural network. An elementary memory size of an elementary memory area intended to store the input data and the output data from the layer is determined for each layer. The elementary memory size is in the range between a memory size for the input data or output data from the layer and a size equal to the sum of the memory size for the input data and the memory size for the output data from the layer. The overall memory size is determined based on the elementary memory sizes associated with the layers. The global memory area contains all the elementary memory areas.

公开(公告)号：US10136393B2

公开(公告)日：2018-11-20

申请号：US15472794

申请日：2017-03-29

Applicant: STMicroelectronics (Rousset) SAS ,  STMicroelectronics SA

Inventor： Pierre Demaj ,  Matthieu Durnerin ,  Laurent Folliot ,  Ludovic Champsaur

IPC: H04W52/02 ,  H04M1/725 ,  H04W4/02 ,  H04W4/04 ,  H04W4/50 ,  H04W4/38 ,  H04L29/08 ,  G06N99/00

Abstract: A control method for real-time scene detection by a wireless communication apparatus equipped with at least one environmental measurement sensor is disclosed. A temporal adjustment of the instants of activation of the detection is based on measurement values delivered by the at least one environmental measurement sensor at instants of measurement.

公开(公告)号：US20170012666A1

公开(公告)日：2017-01-12

申请号：US15042509

申请日：2016-02-12

Applicant: STMICROELECTRONICS (ROUSSET) SAS

Inventor： Pierre Demaj ,  Yoann Bouvet

IPC: H04B3/54 ,  H04L27/26 ,  H04L5/00

CPC classification number: H04B3/54 ,  H04L5/0007 ,  H04L5/0044 ,  H04L27/2601 ,  H04L27/2647

Abstract: A method is for processing an analog channel signal from a transmission channel. The analog channel signal conveys frames, the transmission channel being linear and cyclostationary for a duration of a frame. The method may include converting of the analog channel signal into a digital channel signal, and performing channel estimations for the frame based upon the digital channel signal to generate a sequence of N transfer functions of the transmission channel. Each of the sequence of N transfer functions may be respectively associated with N successive time slices. The method may include decoding at least some symbols of the frame using, for each of the symbols, a transfer function associated with a successive time slice including a respective symbol.

Abstract translation: 一种用于处理来自传输信道的模拟信道信号的方法。 模拟信道信号传送帧，传输信道在帧的持续时间内是线性的和循环平稳的。 该方法可以包括将模拟信道信号转换为数字信道信号，以及基于数字信道信号对帧执行信道估计，以产生传输信道的N个传递函数的序列。 N个传送函数的每个序列可以分别与N个连续时间片相关联。 该方法可以包括使用针对每个符号的与包括相应符号的连续时间片相关联的传递函数来对帧的至少一些符号进行解码。

公开(公告)号：US20230409869A1

公开(公告)日：2023-12-21

申请号：US18316152

申请日：2023-05-11

Applicant: STMicroelectronics ( Rousset ) SAS

Inventor： Laurent Folliot ,  Pierre Demaj

IPC: G06N3/04

CPC classification number: G06N3/04

Abstract: According to one aspect, there is proposed a method for transforming a trained artificial neural network including a binary convolution layer followed by a pooling layer then a batch normalization layer, the method includes obtaining the trained artificial neural network and transforming the trained artificial neural network such that the order of the layers of the trained artificial neural network is modified by displacing the batch normalization layer after the convolution layer.

公开(公告)号：US11593664B2

公开(公告)日：2023-02-28

申请号：US16917414

申请日：2020-06-30

Applicant: STMicroelectronics S.r.l. ,  STMicroelectronics (Rousset) SAS

Inventor： Laurent Folliot ,  Pierre Demaj ,  Emanuele Plebani

IPC: G06N3/10 ,  G06N3/04 ,  G06N3/08

Abstract: A method can be performed prior to implementation of a neural network by a processing unit. The neural network comprising a succession of layers and at least one operator applied between at least one pair of successive layers. A computational tool generates an executable code intended to be executed by the processing unit in order to implement the neural network. The computational tool generates at least one transfer function between the at least one pair of layers taking the form of a set of pre-computed values.

公开(公告)号：US11500767B2

公开(公告)日：2022-11-15

申请号：US16810546

申请日：2020-03-05

Applicant: STMicroelectronics (Rousset) SAS

Inventor： Laurent Folliot ,  Pierre Demaj

IPC: G06F21/00 ,  G06F12/02

Abstract: In accordance with an embodiment, a method for determining an overall memory size of a global memory area configured to store input data and output data of each layer of a neural network includes: for each current layer of the neural network after a first layer, determining a pair of elementary memory areas based on each preceding elementary memory area associated with a preceding layer, wherein: the two elementary memory areas of the pair of elementary memory areas respectively have two elementary memory sizes, each of the two elementary memory areas are configured to store input data and output data of the current layer of the neural network, the output data is respectively stored in two different locations, and the overall memory size of the global memory area corresponds to a smallest elementary memory size at an output of the last layer of the neural network.