7 results about "Computation complexity" patented technology

The invention provides a quick beamforming method capable of improving array resolution and gain, comprising the following steps: adopting the construction of a minimum redundant array to optimize an M-element uniform linear array into a P-element non-uniform linear array; carrying out FFT processing on primitive data of a P-element array; in a frequency domain, constructing a covariance matrix of data based on the uniform linear array in accordance with the array aperture extension characteristics of fourth-order cumulants; carrying out normalization processing on the beam space and carrying out estimation on a Bartlett spatial spectrum. By adopting the array aperture extension characteristics of the fourth-order cumulants, the invention realizes that the optimized element layout form is employed to obtain high resolution and overcomes the defects of high requirements of the original fourth-order cumulant-based methods on snapshots and great computational complexity to enable the computation process to be simple and easy to operate. When the signal to noise ratio is higher than the supercritical signal to noise ratio, the method of the invention has higher array gain than that of conventional beamforming. The normalization processing of the beam space realizes effective inhibition to background interference. The beamforming method of the invention is simple and easy to operate and is especially suitable for project application.

The invention discloses a software defect prediction method and device and electronic equipment, and the method comprises the steps: obtaining a feature vector of to-be-predicted software; and determining a software defect prediction result of the to-be-tested software based on the feature vector and a pre-trained prediction model used for software defect prediction with the prediction model beingobtained based on a gradient lifting algorithm and random forest learning machine training. By adopting the method provided by the invention, the gradient lifting algorithm and the random forest learning machine are used for training to obtain the training model for software defect prediction, so that the software defect prediction result output by the prediction model obtained by training is relatively high in accuracy, and meanwhile, relatively large influence on the calculation complexity is avoided.

The invention discloses an optimal power distribution method in a non-orthogonal multiple access system. The optimal power distribution method comprises the following steps: 1) acquiring a channel state; 2) sorting gain signal-to-noise ratios; 3) calculating a power selection value; 4) allocating transmitting power. According to the invention, the optimal power distribution scheme can be quickly solved through a closed-form solution method; on the premise of ensuring the fairness of the users, the minimum rate of each user in the downlink channel of the non-orthogonal multiple access system can be maximized, the calculation complexity is reduced, the optimal power allocation result can be quickly obtained, and the efficiency of allocating the sending power is improved.

The invention provides a plot correlation distribution method based on a quasi-Newton method. The plot correlation distribution method comprises the following steps: firstly, giving a displacement calculation formula of a flight path under the influence of tangential and normal accelerations on the basis of a uniform acceleration model; secondly, decomposing a displacement change formula to reducecalculation complexity, and establishing an iterative model for solving tangential acceleration and normal acceleration based on a quasi-Newton method; constructing an energy formula again to evaluate the influence degrees determined by different trace point distribution schemes; and finally, giving out a route cross avoidance rule and a minimum energy rule, optimizing a plot allocation scheme, and preventing a plot allocation error.