This paper, presents an extended B-tree data structure and a series of algorithms for satisfying a new requirement of manipulating the concurrent group data at real time. By new algorithm the amount of readings and writings in the manipulation has been decreased greatly, and the efficiency of storage utilization has been increased. Discussion indicates that a database formed by the new data structure and new algorithm has the advantages of a lower tree height, a better efficiency of page utilization, and a little cost of operating overhead as compared to a database formed by B-tree and general algorithm.

In this paper, a segmentation-free learning recognition system for two-dimensional and time-serial binary signals is proposed. This system is constructed by using an array of cells, known as the max-product automata, and can recognize time-serial signals segmentation-freely. Learning is carried out by the learning with the second moment matrix of input vectors. Decisions of this system are made by the majority of categories. Experiments by the computer simulation have given good results.