DISCRETE BIDIRECTIONAL ASSOCIATIVE MEMORY WITH LEARNING FUNCTION

In this paper we propose a new discrete bidirectional associative memory (DBAM) which is derived from our previous continuous linear bidirectional associative memory (LBAM). The DBAM performs bidirectionally the optimal associative mapping proposed by Kohonen. Like LBAM and NBAM proposed by one of the present authors,the present BAM ensures the guaranteed recall of all stored patterns,and possesses far higher capacity compared with other existing BAMs,and like NBAM, has the strong ability to suppress the noise occurring in the output patterns and therefore reduce largely the spurious patterns. The derivation of DBAM is given and the stability of DBAM is proved. We also derive a learning algorithm for DBAM,which has iterative form and make the network learn new patterns easily. Compared with NBAM the present BAM can be easily implemented by software.

自然资源与不动产系统实时双向关联对接的研究与实现

不动产目前包括土地、房产,而自然资源又涵盖了水流、森林、山岭、草原、荒地、滩涂、矿产等资源。近几年政府部门信息化建设发展迅速,而面向公众的不动产系统日渐成熟,自然资源部的成立使信息化的整合在更高的层面、更广的业务范围成为可能,打破由来已久的部门壁垒,信息资源共享、联合审批成为大趋势。本文旨在介绍自然资源与不动产系统实时双向关联对接的实现思路,通过编码对接、数据对接、权限对接、接口对接、功能对接最终达到实时双向管理对接,让面向公众访问量庞大的不动产系统不受试点中经常发布更新的自然资源系统影响,从而满足国家自然资源的顶层设计。