In order to optimize the pattern synthesis of multiple input and multiple output (MIMO) radar, immune mechanism is adopted to overcome the premature risk of differential evolution (DE) algorithm, namely immune differential evolution (IDE). Firstly, the modeling of MIMO radar is introduced by encoding the position of array in the binary. Secondly, the immune mechanism is employed to improve the DE. In IDE, two parameters are self-adapted for the mutation operator by immune mechanism to enhance the convergence ability of DE, including scaling factor and crossover rate. Several experiments are conducted to analysis the performance of IDE. The simulation results show that the IDE with variable parameters can get optimal results in MIMO radar with lower the peak side-lobe level (PSLL) and maintain the diversity with stronger convergence ability and shorter calculation speed.

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In this article, a cognitive framework for observing learning activities based on human-computer coupling is proposed. The observation is based on the vectorization of a learning situation along with human-computer interaction factors. An evolutionary high-dimensional topology of learning cognitive flow is introduced for human-computer interaction. In addition, the authors have selected a tree topology as the topological structure of a low-dimensional learning space to process the observations for online learning. Furthermore, the mechanism for the BSM (brain cognitive body-situation of coupling-manifold of information) the coupling morphism is presented. The principle for the coupled observation of objects in a cognitive or learning manifold is proposed. Finally, a special system for teaching and learning is programmed to observe and evaluate learning and mental arithmetic training processes. This system not only provides students with a new ergonomic learning model but also records the students' learning processes. Thus, the teachers can summarize the knowledge points automatically rather than manually.

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To lower the side lobe level of MIMO (Multi-input Multi-output) radar, a new method, diffenence set and diffderential evolution (DSDE), was proposed. The newly proposed method can arrange the location of the linear MIMO radar antenna arrays by differential set (DS) and optimize the excitation amplitude of each antenna by Differential Evolution (DE). DS is a kind of analysis calculation method, which has faster calculation speed than intelligent optimization methods and has solid optimization ability in thinned antenna array optimization problems. Besides, DE is one of the best stochastic optimization methods which can keep the diversity and avoid premature of the population. Consequently, the proposed DSDE can achieve high performance in the arrangement of arrays and excitation amplitude optimization. Numerical experiments are conducted to test the performance of the proposed algorithm, and the results showed that the analysis optimization method and stochastic optimization method are suitable for solving the problem of pattern synthesis of MIMO radar and keep the diversity with better convergence.