Patent classifications
G06F17/147
Unknown object classification through signal transform set
Various embodiments are described that relate to classification of an unknown object. A time series signal associated with an unknown object can be obtained from a sensor. The time series signal can be subjected to a transform set, such as a Fourier transform and a discrete cosine transform, to produce a transform outcome. Based, at least in part, on the transform outcome, the unknown object can be classified.
METHOD AND DEVICE FOR PROCESSING VIDEO SIGNAL BY USING TRANSFORM HAVING LOW COMPLEXITY
An embodiment of the present specification provides a method and device for processing video data. A method for processing a video signal according to an embodiment of the present specification may comprise the steps of: acquiring a transform index related to one of a plurality of transform combinations including combinations of one or more transform kernels for transforming of a current block of the video signal; deriving a transform combination including a vertical transform and a horizontal transform related to the transform index; and applying each of the vertical transform and horizontal transform of the transform combination to the current block, wherein the transform kernels include DST-7 or DST-8, the DST-7 or DST-8 is designed on the basis of a discrete Fourier transform (DFT) to which a scale value in the form of a power of 2 related to a bit length of a transform coefficient has been applied, and the transform kernels are designed using the DFT to which the scale value has been applied, so as to enable reduction of a calculation complexity for transform.
Unified forward and inverse transform architecture
Multiple transform sizes improve video coding efficiency, but also increase the implementation complexity. Furthermore, both forward and inverse transforms need to be supported in various consumer devices. Embodiments provide a unified forward and inverse transform architecture that supports computation of both forward and inverse transforms for multiple transforms sizes using shared hardware circuits. The unified architecture exploits the symmetry properties of forward and inverse transform matrices to achieve hardware sharing across different the transform sizes and also between forward and inverse transform computations.
FAST METHOD FOR IMPLEMENTING DISCRETE SINE TRANSFORM TYPE VII (DST 7)
A method and apparatus for decoding a video sequence using a discrete sine transform (DST) type-VII transform core includes generating a set of tuples of transform core elements associated with an n-point DST-VII transform core. A first sum of a first subset of transform core elements of a first tuple is equal to a second sum of a second subset of remaining transform core elements of the first tuple. The n-point DST-VII transform core is generated based on generating the set of tuples of transform core elements. A transform on a block is performed using the n-point DST-VII transform core.
Signal processor, filter, control circuit for power converter circuit, interconnection inverter system and PWM converter system
A signal processor is configured to perform a process equivalent to performing a series of fixed-to-rotating coordinate conversion, a predetermined process and then rotating-to-fixed coordinate conversion, while maintaining linearity and time-invariance. The signal processor performs a process given by the following matrix G:
Optimization method for implementation of mel-frequency cepstral coefficients
An optimization method for an implementation of mel-frequency cepstral coefficients is provided. The optimization method includes the following steps: performing a framing step, including using a 400×16 static random access memory to temporarily store a plurality of sampling points of a sound signal with overlap, and decomposing the sound signal into a plurality of frames. Each of the plurality of frames is 400 of the sampling points, there is an overlapping region between adjacent two of the plurality of frames, and the overlapping region includes 240 of the sampling points. The optimization method further includes performing a windowing step, which includes multiplying each of the plurality of frames by a window function in a bit-level design, and the optimization method includes performing a fast Fourier transform (FFT) step, which includes applying a 512 point FFT on a frame signal to obtain a corresponding frequency spectrum.
Target tracking method, system, device and storage medium
The present invention provides a target tracking method, system, device and storage medium, which includes: Determining a target area based on the current frame of a training sample, extracting and fusing histogram of oriented gradient (HOG), color naming (CN), and color space HSV features of the target area to obtain a target template; Determining a target function according to the target template and a spatial regularization weight factor; Introducing the Sherman-Morrison formula into the alternating direction method of multipliers (ADMM) to accelerate the solution of the target function and obtain the response value; Iterating the target tracking model when the response value meets the preset confidence threshold until training is completed to obtain a trained target tracking model, and tracking the target in the video to be observed by using the trained target tracking model.
METHODS AND APPARATUS FOR PERFORMING VIDEO PROCESSING MATRIX OPERATIONS WITHIN A MEMORY ARRAY
Methods and apparatus for performing video processmg matrix operations within a memory fabric. Various embodiments of the present disclosure are directed to converting a memory array into a matrix fabric for discrete cosine transform (DCT) matrix transformations and performing DCT matrix operations therein. Exemplary embodiments described herein perform DCT matrix-matrix multiplication operations within a memory device that includes a matrix fabric and matrix multiplication unit (MMU). In one embodiment, matrix-matrix multiplication operations are obtained using separate matrix-vector products. In one exemplary embodiment, the matrix fabric uses a “crossbar” construction of resistive elements. Each resistive element stores a level of impedance that represents the corresponding matrix coefficient value. The crossbar connectivity can be driven with an electrical signal representing the input vector as an analog voltage. The resulting signals can be converted from analog voltages to a digital values by an MMU to yield a vector-matrix product. In some cases, the MMU may additionally perform various other logical operations within the digital domain.
Multiplicative filter network
A computer-implemented method includes applying a filter to input data based on an initial set of parameters to generate an initial feature map. The filter is configured to activate a filter function that involves a periodic function. The method includes performing a first linear transform on the initial feature map based on a subset of a first set of parameters to generate a first linear transform. The method includes applying the filter to the input data based on another subset of the first set of parameters to generate a first feature map. The method includes performing a multiplicative operation on the first linear transform and the first feature map to generate a first product. The method includes performing a second linear transform on the first product based on a subset of a second set of parameters to generate a second linear transform. The method includes generating output data that takes into account at least the second linear transform. The output data is a quantity of interest that is generated with high fidelity. The output data is specified by the input data over a space that defines the output data.
LINE GRAPH TRANSFORMS (LGT) USING 8-BIT AND 10-BIT CORES
A method, computer program, and computer system is provided for coding video data. Video data is received. One or more transform cores corresponding to a transform associated with the video data are identified. The one or more transform cores include one or more of a line graph transform (LGT) and a discrete sine transform (DST) The video data is decoded based on the identified transform core. The transform cores correspond to one or more from among an 8-bit transform core and a 10-bit transform core. The transform corresponds to one or more from among a 2-point transform, a 4-point transform, an 8-point transform, and a 16-point transform.