Hangzhou Dianzi University

A method for semiconductor bridge current protection based on vanadium dioxide thick-film thermistor is provided, which relates to the field of semiconductor bridge current protection technologies. A copper, nickel, or gold interdigitated electrode is deposited on an aluminum oxide ceramic substrate. A vanadyl acetylacetonate methanol solution is sprayed onto a surface of the heated interdigitated electrode to obtain a vanadium dioxide thermistor device. This device is connected in parallel with a semiconductor bridge to achieve thermistor-based semiconductor bridge current protection. By adjusting a synthesis method and process, vanadium dioxide with a relatively single valence state can be synthesized, thereby achieving one-step synthesis of M-phase vanadium dioxide directly on the interdigitated electrode. This preparation method avoids a cumbersome process of first preparing vanadium dioxide powder and then transferring it onto the surface of the interdigitated electrode, and the vanadium dioxide can also be more stably bonded to the interdigitated electrode surface.

A diagonalized spatial smoothing coherent DOA estimation method based on non-circular signals includes the following steps: firstly, receiving non-circular signals through a uniform linear array antenna to obtain received information; according to non-circular characteristics of the signals, concatenating the received information and the conjugate to form extended received information, and calculating the covariance matrix; then extracting subarrays from the covariance matrix diagonally, and performing augmented spatial smoothing operation on the extracted subarrays; splicing the results of smoothing operations to generate a new covariance matrix, and performing eigenvalue decomposition on the new covariance matrix to obtain a noise subspace; finally, based on the noise subspace, estimating the DOA of the non-circular signal by the reduced-dimension MUSIC algorithm.

A method for accelerating fast Fourier transform (FFT) based on field programmable gate array is provided. A sequence requiring N-point FFT is decomposed equally into 4 subsequences. The 4 subsequences are processed through 4 parallel FFT intellectual property (IP) cores. Finally, an arithmetic operation is performed on the processed data and twiddle factor data pre-stored in a memory to obtain a result of the N-point FFT of an original sequence. An FFT decomposition module, a twiddle factor storage module, and an operation processing module are provided. Through the processing method, a time delay consumed by an N-point FFT operation can be reduced, and excellent application value can be achieved in a high-speed digital signal processing system.

The present disclosure provides a task-independent brainprint recognition method based on feature disentanglement by decorrelation. Existing methods fail to mine inherent identity information of a brain, leading to poor robustness of brainprint recognition in a scenario across tasks and difficulty of promotion thereof in practical use. The present disclosure firstly uses two branch networks to perform coarse-grained decomposition of identity information and task related information in an electroencephalogram (EEG). Secondly, in consideration of an influence of a task state on the identity information, a decorrelating method is employed such that the identity information and the task related information are independent as much as possible. Finally, a brainprint feature in the EEG is fully utilized for classification by adversarial self-supervision. The method of the present disclosure is good in performance and capable of realizing efficient task-independent brainprint recognition, and is a brainprint recognition method robustly useful in the real life.

The present application provides a method for querying a high-connectivity shortest influence path between users, a device, and a product. The method includes: constructing an indexed linked list data structure based on an obtained social network graph; determining, based on the indexed linked list data structure, a start node, a target node, and a path connectivity in a current iteration, whether there is a shortest influence path satisfying the path connectivity in the current iteration; if yes, updating a minimum path connectivity in a previous iteration and determining the path connectivity in the current iteration based on the minimum path connectivity; or if no, determining the path connectivity in the current iteration as a maximum path connectivity in the previous iteration; and continuing the iteration based on the maximum path connectivity and the minimum path connectivity until a high-connectivity shortest influence path is determined.

A detonator for an explosive material is described. The detonator includes a semiconductor bridge, coupled with the explosive material, including thermal feedback mechanism is provided via one or more thermistors. The mechanism includes a semiconductor bridge with a polysilicon resistor, at least a pair of thermistors and a pair of diodes provided to prevent accident static discharge. The two thermistors are disposed to be substantially close to or sandwich the polysilicon resistor. When the temperature surrounding the polysilicon resistor is getting upwards, the temperature surrounding the thermistors is equally going up. When the temperature reaches a critical point, but below the threshold of the polysilicon resistor, the resistance of the thermistors drops suddenly or drastically, causing the current driving up the temperature of the polysilicon resistor to divert through the VOX temp resistors. Subsequently the current going through the polysilicon resistor is reduced, causing the temperature to drop downwards.

The present application provides a method for querying a high-connectivity shortest influence path between users, a device, and a product. The method includes: constructing an indexed linked list data structure based on an obtained social network graph; determining, based on the indexed linked list data structure, a start node, a target node, and a path connectivity in a current iteration, whether there is a shortest influence path satisfying the path connectivity in the current iteration; if yes, updating a minimum path connectivity in a previous iteration and determining the path connectivity in the current iteration based on the minimum path connectivity; or if no, determining the path connectivity in the current iteration as a maximum path connectivity in the previous iteration; and continuing the iteration based on the maximum path connectivity and the minimum path connectivity until a high-connectivity shortest influence path is determined.

The application provides a method for generative heterogeneous logic optimization based on critical path partitioning. The method includes: converting a digital logic circuit into an And-Inverter Graph (AIG) format; partitioning the AIG using reinforcement learning based on critical path information of the circuit to obtain critical-path-aware partitions so as to reduce influence of critical path changes brought by the partitioning on timing performance; respectively and automatically exploring an optimized structure and synthesis flow suitable for each partition using the reinforcement learning method; selecting optimization operators for various structures using a reinforcement learning agent guided by area-delay metrics and optimizing each partition; and merging the optimized partitions in the AIG format. In the application, the digital logic circuit is partitioned based on critical paths, and reinforcement learning is used to explore and optimize structures and strategies based on area and delay.

Provided is an ensemble learning (EL)-based speaker verification method. The method includes: data acquisition and preprocessing; selecting and training a group of basic models, and optimizing model parameters; performing similarity scoring on an acquired pair of speaker feature embedding via the group of basic models; constructing a detection cost function (DCF); generating a weight, and performing weighted fusion on scoring results of the group of basic models based on the weight, to obtain a final ensemble model for speaker verification; based on a near-speaking or far-speaking test scenario of a voice sample, the scenario is distinguished and input into the ensemble model, to obtain a final similarity score after weighted fusion; and determining, based on a threshold, whether there is a same speaker, where if the similarity score is greater than the threshold, it is determined that there is a same speaker.

A local neurogeometric learning based light field super-resolution method in spatial-angular continuous domain includes: S 1 , sending a sparse and low-resolution sub-aperture image array of the light field image into the spatial-angular aware geometric encoder module to obtain spatial-angular aware latent geometric codes; S 2 , sending the spatial-angular aware latent geometric codes into the local neural geometric learning module to obtain latent geometric codes of the spatial-angular continuous domain; S 3 , sending the latent geometric codes of the spatial-angular continuous domain into the extended rendering module to obtain a dense and high-resolution light field image; S 4 , setting a loss function for the neural network model; S 5 , using a trained neural network model to perform a light field super-resolution task test in the spatial-angular continuous domain on a test data set. The method can realize the super-resolution of the light field image in both spatial dimension and angular dimension at any scale.