Recognition Of The Collaborative Multi-attribute Goals Based On Rough Set Theory

We can use the attributes which make things different from others to distinguish object, so we could believe that attributes recognition is the main work of target recognition. Rough set theory is a powerfull tool for dealing with the data mining, and we could use it to work in target recognition, in particular to deal with identification for poly-attributes issue.So in this thesis, we will use the rough set theory to build a new target system for improve the accuracy of the target recognition.The main results are as follows:1.In this thesis, we use a information system to describe the object. The information system is defined as IS = {U , A, V , f}. U : U = { x1 , x2 ,..., xn} is the set of objects; C : C = {a | a∈C} is the set of attributes; V : V =∪V j,(1≤j≤m) is the attribute value; f : f = { f j | f j : Uâ†'V j,(1≤j≤m)} is the function which is connection attributes and attribute value. This descriptive method provides sufficient data for target recognition.2.The. algorithm of recognition system as follow: Reduce the attribute and attribute value according to mission requirements. Define the degree of importance, valuate the attribute based on the degree of importance. Use the sum of valuation as the standard for target recognition.3.Use the simulation results which are simulated in 5dB SNR for AWGN channel to prove this new recognition system has better performance. This paper discuss about the factors which affect the performance of recognition system.