Stmicroelectronics S.r.l.

Stmicroelectronics International N.v.

Beatrice Rossi

Pasqualina Fragneto

Diego Carrera

Giacomo Boracchi

Daniele Zambon

Giuseppe Desoli

Emiliano Mario Piccinelli

Marco Passoni

Subarna Tripathi

Luca Magri

Francesca Carminati

Valentina Arrigoni

Paolo Giugni

Annalisa Aurigemma

Elena Tagliabue

Lidia Moioli

Mauro Fumagalli

Federica Arrigoni

Matteo Colella

Luca Frittoli

A method of operating a PMUT electro-acoustical transducer, the method comprising: applying over an excitation interval to the transducer an excitation signal which is configured to emit corresponding ultrasound pulses towards a surrounding space, acquiring at a receiver reflected ultrasound pulses as reflected in said surrounding space, generating a reference echo signal, performing a cross-correlation of said acquired received ultrasound pulses with said reference echo signal, performing a measurement based on the cross-correlation results, in particular a measurement of the time of flight of the ultrasound pulses, wherein said reference echo is obtained by finding an oscillation frequency of the transmitter on the basis of a transmitter ringdown signal, finding an oscillation frequency of the receiver on the basis of a receiver ringdown signal, performing a frequency tuning respectively on the transmitter and the receiver on the basis of said respective oscillation frequencies, then sweeping an input frequency of the transmitter to find a frequency of the maximum displacement in the ringdown signal, performing a frequency tuning of the receiver at said frequency of the maximum displacement in the ringdown signal of the transmitter.

Method of operating electro-acoustic transducers, corresponding circuit and device

A method of operating neural networks such as convolutional neural networks including, e.g., an input layer, an output layer and at least one intermediate layer between the input layer and the output layer, with the network layers including operating circuits performing arithmetic operations on input data to provide output data. The method includes: selecting a set of operating circuits in the network layers, performing arithmetic operations in operating circuits in the selected set of operating circuits by performing Residue Number System or RNS operations on RNS-converted input data by obtaining RNS output data in the Residue Number System, backward converting from the Residue Number System the RNS output data resulting from the RNS operations.

Method of operating neural networks, corresponding network, apparatus and computer program product

A device includes image generation circuitry and a convolutional neural network. The image generation circuitry, in operation, generates a binned representation of a wafer defect map (WDM). The convolutional-neural-network, in operation, generates and outputs an indication of a root cause of a defect associated with the WDM based on the binned representation of the WDM and a data-driven model associating WDMs with classes of a defined set of classes of wafer defects.

Wafer manufacturing system, device and method

A heart-rate associated with a heartbeat signal is determined. A transform is selected based on the determined heart-rate associated with the heartbeat signal and a reference heart-rate associated with a dictionary of a sparse approximation model. The transform is selected independent of other factors associated with generation of the heartbeat signal. The selected transform is applied to the dictionary of the sparse approximation model, generating an adjusted dictionary of the sparse approximation model. Anomalous heartbeats in the heartbeat signal are detected using the adjusted dictionary of the sparse approximation model.

Method for the detecting electrocardiogram anomalies and corresponding system

A heartrate monitor detects heartbeats in a test signal. A local heartrate and an energy of acceleration are associated with the detected heartbeats. Detected heartbeats are included or excluded from a test set of heartbeats based on the local heartrate and energy of acceleration associated with the respective heartbeats. Anomalous heartbeats in the test set of heartbeats are detected using a sparse approximation model. The heartrate monitor may detect heartbeats in a training heartbeat signal. A reference heart rate and an energy of acceleration are associated with detected beats of the training heartbeat signal and selectively included in a set of training data based on the heart rate and energy of acceleration associated with the detected beat in the training heartbeat signal. A dictionary of the sparse representation model may be generated using the set of training data.

The present disclosure is directed to systems and methods to perform absolute rotation estimation including outlier detection via low-rank and sparse matrix decomposition. One example method includes obtaining a relative rotation estimates matrix that includes a plurality of relative rotation estimates. The method includes determining values for a low-rank matrix that result in a desirable value of a cost function that is based on a low-rank and sparse matrix decomposition of the relative rotation estimates matrix. The cost function includes the low-rank matrix and a sparse matrix that is nonzero in correspondence of one or more outliers of the plurality of relative rotation estimates. The method includes determining an absolute rotations matrix that includes a plurality of absolute rotations based at least in part on the values of the low-rank matrix that result in the desirable value of the cost function.

Absolute rotation estimation including outlier detection via low-rank and sparse matrix decomposition

An embodiment is a computer-implemented method for detecting a straight line in a digital image comprising a plurality of pixels comprising the steps: detecting an edge in the digital image, generating a first straight line which passes through a first pixel of the detected edge, generating a second straight line which passes through a second pixel of the detected edge, which is different from the first pixel, determining at least two intersections with a boundary of the digital image for each generated straight line, determining a set of two parameter values for each generated straight line based on the respective determined at least two intersections, wherein the set of two parameter values uniquely determines the respective generated straight line, and detecting the straight line in the digital image based on the determined sets of two parameter values.

Method for detecting a straight line in a digital image

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Milan, Italy

Beatrice Rossi