Abstract: 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 frequ

Abstract: A method of performing an electro-thermo simulation includes defining a non-linear heat diffusion problem for at least a portion of a semiconductor device to be modeled, performing a finite volume discretization of the non-linear heat diffusion problem, reformulating a non-linear term of the discretized non-linear heat diffusion problem to decrease dimensions thereof, performing a hyper reduction of the reformulated non-linear term, and recovering the non-linear heat diffusion problem for the portion of the semiconductor device, and manufacturing the modeled semiconductor device.

Abstract: 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.

Abstract: A method, comprising: providing an ANN processing stage having a plurality of processing layers with respective parameters including at least one set of weight parameters, at least one input, resp. output, activation parameter and at least one activation function parameter; setting to an integer value a dimensional parameter of a lattice having a plurality of lattice points and identified by a set of basis vectors; selecting a set of weight parameters of a respective processing layer; vectorizing the selected set of weight parameters producing a set of weight vectors arranged as items of a matrix of weight vectors; normalizing the matrix of weight vectors; applying lattice vector quantization, LVQ, processing to the matrix of normalized weight vectors, producing a codebook of codewords; indexing by encoding codewords of the codebook as a function of the lattice, producing respective tuples of indices.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: An embodiment of a method is disclosed for encoding a digital video signal including a first video sequence and a second video sequence jointly forming a stereo-view digital video signal. The method includes: subjecting the first video sequence to discrete cosine transform, quantization and run-length coding to produce a sequence of blocks of non-zero digital levels representative of the first video sequence, subjecting the second video sequence to discrete cosine transform, quantization, run-length coding and variable length coding to produce digital messages representative of the second video sequence, merging the bits of the digital messages into the sequence of blocks of digital levels by substituting the bits of the digital messages for respective Least Significant Bits of e.g. the last digital level in the blocks representative of the first video sequence to produce an encoded digital video signal representative of the first video sequence and the second video sequence.