The invention relates to a quick high-efficiency video coding (HEVC) intra-frame coding unit and pattern decision method which comprises the following steps: (1) the effective length N of a threshold value is set; (2) a first frame of a video sequence is normally coded, and the final coding depth and the discrete total variation (DTV) value of each largest coding unit (LCU) are stored in a cache region; (3) the DTV values in the cache region are counted, and a threshold value T1 and a threshold value T2 are worked out according to the depth range; (4) a quick pattern searchalgorithm based on direction gradient is adopted on the remaining N-1 frames according to the current DTV values of the LCUs and the threshold values at each depth search, with low-probability depth skipped; and (5) the (N+1)th frame is set as the first frame, and the steps (1), (2) (3) and (4) are repeated until all the frames are coded. The method adopts adaptive DTV threshold decision, the number of searched macro block units is reduced, the process of pattern search is simplified by adopting features based on direction gradient, and the coding speed is increased.
The invention provides a large-spacing phased-array antenna grating lobe suppression method. The method comprises the following steps: constraining the positions of array elements; constructing a fitness function and a fitness function optimization model; selecting and crossing: selecting a certain proportion of individuals before sorting as parents for generating a new generation of population; then performing crossover operation on the population of the generation to obtain a new generation of population; mutation: for each gene of each population, randomly generating a number r between [0,1], and if r is less than Pm, replacing r with a randomly generated parameter in a value domain, where Pm is a mutation probability; and optimal solution calculation: carrying out position optimization on the large-spacing planar array by utilizing a genetic algorithm, taking an optimization result as an initial solution of a mode search algorithm, and further optimizing to find an optimal solution under the current condition. The array obtained by constraining the positions of the array elements in the optimization process is easy to implement in engineering, the grating lobe suppression effect is good, and the grating lobe can be suppressed to-8dB or below under the condition that the minimum spacing of the array elements is 3 lambda.
The invention discloses an automatic programming method and system for natural languagemachine thinking. After a task book is obtained, the following steps are sequentially carried out: S1, converting and expressing a task book text; S2, establishing a corresponding relation library; S3, externally inputting or automatically compiling a task book text, and interpreting, defining and understandingthe task book to be solved; S4, searching an algorithm module library according to the problem type and the problem framework composition mode, and designing an algorithm for solving the problem, a design program and a selected algorithm according to the algorithm module library; S5, entering a natural language generation type system, and outputting an instruction to enter programmingsoftware orenter any programming language for programming to obtain a program; And S6, running the program, and checking an output result of the program. Therefore, the machine automatically generates a specific program capable of completing the target after receiving the demand description about the target to be realized by the designed program. The method is a creative artificial intelligence technology,and has a great commercial value.
The invention discloses a photovoltaic system MPPT (Maximum Power Point Tracking) method based on a leapfrog and pattern search neural network, which comprises the following steps of: (1) obtaining the temperature and irradiance of a photovoltaic module, and obtaining a maximum power point reference voltage by adopting a neural network; (2) enabling the controller to obtain an output quantity according to an error between the reference voltage and the measurement voltage of the photovoltaic module; (3) enabling an enhanced disturbance observer P& Q to obtain the control quantity of the chopper circuit according to the measured voltage, the measured current and the output quantity of the controller, so that the photovoltaic system stably works at the maximum power point along with the illumination change. According to the method, a hybrid recombination leapfrog and pattern searchalgorithm is adopted to optimize the maximum power point tracking based on the neural network in the photovoltaic system; the method has excellent performance in response speed and precision, and can provide the highest tracking efficiency and the fastest response time under the condition that the steady state and the irradiance are continuously changed, and the response time is 11 seconds.