Abstract: This paper presents a new algorithm based on the Shortest Distance of perception，and puts forward the process by analyzing the relation between soluble vector and normal vector.Simultaneously，it compares the new algorithm proved by examples with the LMSE and the learning algorithm of variable paces.Consequently，on linearity separable，it shows that the new algorithm SDA can solve convergence in all the traditions and enhance the speed of calculation.

Key words: the perception approach, soluble vector, normal vector, the limited square error, the learning algorithm of perception with variable paces

摘要： 分析了模式空间中解向量和法向量的关系，提出了一种新的基于最短距离的感知器算法。并对该算法和最小平方误差法以及变步长学习法进行了分析和比较。结果表明，在线性可分的前提下，该算法有效解决了收敛性的问题，提高了计算速度。

关键词: 感知器, 解向量, 法向量, 最小平方误差法, 变步长学习法