Now the research of it has made a great achievement , based on it we studied the feature of the binary complementary sequences . the feature sequences of complementary sequences are introduced in this paper . every complementary sequence has two kinds of feature sequences 目前互补序列的研究取得了丰富研究成果，在这些研究成果的基础上，进一步对互补序列的特性进行研究，并引入了互补序列的特征序列的概念，定义每个互补序列包含两种特征序列，分别记为1 -特征序列和2 -特征序列。
Besides property , method and eventset we give other two kinds of feature interfaces ( ilifecycle and ipersist ) for component wrappers . to each component model , there should be a corresponding component wrapper , and every wrapper should implement the interfaces provided in the generic component model 其次，在构件包装器的设计方面，除了属性、方法、事件三种特征接口外，还定义了生命周期特征和持久性特征的接口，解决了原有构件包装器设计中的特征损失问题。
Finally , combining the two extraction methods with the two classification methods , the thesis put forward four models of palmprint recognition : k - l + ld model , k - l + nn model , nn + ld model and nn + nn model . the experiments show the accuracy , efficiency and the fault tolerance ability of these models . in terms of their characteristic , we can apply them in various fields 论文把两种特征提取方法和两种分类器设计方法进行结合，提出k - l变换与最小分类器、 k - l变换与bp神经网络分类器、线性神经网络与最小分类器、线性神经网络与bp神经网络分类器四种组合，最后对四种识别方法进行比较，根据它们识别的准确率、效率以及容错能力对识别结果进行分析，总结出各种方法的优缺点，根据它们的特点，提出在不同方面的应用。
According to commonly steps of speech recognition , the key methods of speech recognition is discussed : a ) firstly , preprocessing and feature extraction in speech recognition is studied . we studied two important speech analysis methods and extracted two key features for speech recognition : mfcc and lpcc . on the base of the research we improve the algorithm and experiment with new method 论文根据语音识别的一般流程，主要针对语音识别系统的关键技术进行探讨： ( 1 )首先对语音信号的预处理和特征提取问题进行讨论。分析了当前最常用的两种特征参数， mfcc和lpcc ，在此基础上对语音识别系统预处理和特征提取作了一些改进，并给出相应的实验验证。
