50results about How to "Effectively delete" patented technology

The invention discloses a method for reducing brain wave medical record signals based on a three-layer cross game energy tree. In this method, two adjacent three-layer cross-game energy trees Ti and Tj are firstly designed, and the selfish game is realized in the same main layer and the cross-cooperative game is realized between different main layers. The depth-first search strategy is used to select the two game energy trees. The global optimal elites Elitisti_c and Elitistj_c; then assign the elite energy gain matrix PMENn×n to the optimal elites, and enhance the elites to obtain adaptive Nash energy exploration and development balance performance in the main layer; finally realize the cross-game energy reduction of brainwave medical record signals , so that the optimal elite converges to the optimal Nash equilibrium point of each main layer under the drive of the elite energy vector Γ, and achieves the balance of the reduction accuracy of the brainwave medical record signal, thereby outputting the global optimal brainwave medical record signal. The invention can effectively improve the reduction efficiency of brainwave medical record signals, provide important methods for brainwave signal noise elimination, feature extraction and analysis, etc., and has strong application value for brain disease diagnosis and auxiliary treatment.

The invention discloses a tumor key gene identification method based on particle swarm optimization and a marking criterion. The method comprises the steps that one gene marking criterion is defined to acquire gene classification ability information so as to filter genes with a low correlation to a tumor category; and the Metropolis criterion is utilized to improve a particle swarm optimization (PSO) algorithm in combination with the gene classification ability information so as to realize identification of tumor key genes. The new method for gene classification information and PSO improvement overcomes the defect that a traditional method for identifying tumor key genes based on PSO is prone to fall into a locally optimal solution, gene subsets in a smaller number and with a high correlation to the tumor category can be selected, and therefore the method is beneficial for improving subsequent tumor identification.