This invention relates to a method of classification of images among different classes comprising: performing a dimensionality reduction step for said different classes on a training set of images whose classes are known, and then classifying one or more unknown images among said different classes with reduced dimensionality, said dimensionality reduction step being performed on said training set of images by machine learning including processing, for at least a first matrix and for at least a second matrix, a parameter representative of a product of two first and second matrices to assess to which given classes several first given images respectively belong: first matrix representing the concatenation, for said several first given images, of the values of the pixels of each said first given image, second matrix representing the concatenation, for said several first given images, of the values of differences between the pixels of each said first given image and the pixels of a second given image different from said first given image but known to belong to same class as said first given image, wherein: a quantum singular value estimation is performed on first matrix, a quantum singular value estimation is performed on second matrix, both quantum singular value estimation of first matrix and quantum singular value estimation of second matrix are combined together, via quantum calculation, so as to get at a quantum singular value estimation of said product of both first and second matrices, said quantum singular value estimation of said product of both first and second matrices being said parameter representative of said product of two first and second matrices processed to assess to which given classes said several first given images respectively belong.

A Hough processor comprises a pre-processor and a Hough transformation unit. The pre-processor is configured to receive a plurality of samples respectively comprising an image and in order to rotate or reflect the image of the respective sample. The Hough transformation unit is configured to collect a predetermined searched pattern in the plurality of samples on the basis of a plurality of versions. The Hough transformation unit comprises a characteristic being dependent on the searched pattern, which is adjustable according to the searched pattern.

An analog circuit fault feature extraction method based on a parameter random distribution neighbor embedding winner-take-all method, comprising the following steps: (1) collecting a time-domain response signal of an analog circuit under test, wherein the input of the analog circuit under test is excited by using a pulse signal, a voltage signal is sampled at an output end, and the collected time-domain response signal is an output voltage signal of the analog circuit; (2) applying a discrete wavelet packet transform for the collected time-domain response signal to acquire each wavelet node signal; (3) calculating energy values and kurtosis values of the acquired wavelet node signals to form an initial fault feature data set of the analog circuit; and (4) analyzing the initial fault feature data by the parameter random distribution neighbor embedding winner-take-all method, to acquire optimum low-dimensional feature data. The invention effectively reduces redundancy and interference elements in the fault features, and greatly improves degree of separation of different fault features and degree of polymerization of samples of same fault category.

Embodiments of this invention include computer-implemented methods for use of Haar wavelet transforms (HWT) to pre-process video frames that can then be compressed using a codec to produce a compressed video frame. A compressed video frame can then be transmitted, decompressed, post-processed and displayed in their original size and quality, thereby producing real-time high-quality reproduction of video sequences. Devices can implement methods of this invention and include mainframe computers, desktop computers, personal computers, laptop computers, tablet computers, wireless computers, television sets, set top boxes, cellular telephones, and computer readable media. Computer implemented steps can be easily and efficiently implemented in multicore parallel hardware architectures.

Mechanisms are disclosed for performing efficient lossless encryption and decryption to reduce power consumption and improve the efficiency of processing streams of digital data. An input data stream associated with a stream of input data is received. A discrete wavelet transform is applied to a first serial input data value in the input data stream. Distributed components of the first serial input data value are distributed by computing a cumulative probability that the first serial input data value is less than or equal to a power-of-two range value associated with a power-of-two probability distribution function. An entropy encoded encryption value is computed based on a range variant asymmetrical numeral system based on the power-of-two probability distribution function. The entropy encoded encryption value is unloaded based on one or more computed next states. Compressed serial output data streams are compressed based on the unloaded entropy encoded encryption value.

A 3D image analyzer for the determination of a gaze direction or a line of sight (having a gaze direction vector and a location vector, which e.g. indicates the pupil midpoint and where the gaze direction vector starts) in a 3D room is configured to receive one first set of image data and a further set of image information, wherein the first image contains a pattern, which displays a three-dimensional object from a first perspective into a first image plane, and wherein the further set contains an image having a pattern, which displays the same three-dimensional object from a further perspective into a further image plane, or wherein the further set has an image information and/or a relation between at least two points in the first image and/or at least a position information. The 3D image analyzer has a position calculator and an alignment calculator and calculates therewith a gaze direction in a 3D room.

Embodiments described herein ensure differential privacy when transmitting data to a server that estimates a frequency of such data amongst a set of client devices. The differential privacy mechanism may provide a predictable degree of variance for frequency estimations of data. The system may use a multibit histogram model or Hadamard multibit model for the differential privacy mechanism, both of which provide a predictable degree of accuracy of frequency estimations while still providing mathematically provable levels of privacy.

The invention provides a method for generating and analyzing random sample values. The method includes generating a random population array with a distribution and generating an array of random number coefficients by decomposing the random population array distribution using mean and variance. The array of random number coefficients is normalized and the normalized samples and antithetic samples may be mapped to the distribution of the random population array. The mapped, normalized samples and mapped normalized antithetic samples are arranged into a Walsh pattern.

A 2D image analyzer includes an image scaler, an image generator and a pattern finder. The image scaler is configured to scale an image according to a scaling factor. The image generator is configured to produce an overview image including a plurality of copies of the received and scaled image, wherein every copy is scaled about a different scaling factor. Thereby, the respective position can be calculable by an algorithm, which considers a gap between the scaled images in the overview image, a gap of the scaled image towards one or more borders of the overview image and/or other predefined conditions. The pattern finder is configured to perform a feature transformation and classification of the overview image in order to output a position at which an accordance of the searched pattern and the predetermined pattern is maximal. A post-processing unit for smoothening and correcting the position of local maxima in the classified overview image may also be provided.

An electronic device is described which has a sensor panel comprising a plurality of transmit electrodes configured to form an electric field when driven and a plurality of receive electrodes configured to measure signals received from the transmit electrodes. The electronic device has a sensor panel control module configured to apply a driving signal to each of the transmit electrodes, and to compute the driving signals using orthogonal frequency division multiplexing to obtain a plurality of orthogonal subcarrier signals, and configured to apply a Hadamard matrix transform to the orthogonal subcarrier signals to compute final signals for driving the transmit electrodes.