【摘要】 贝叶斯决策理论在模式识别、信号检测中得到了非常广泛的应用。但这一理论的应用是以己知类条件概率密度为前提。本文提出了类条件概率密度随机变量（特征）空间离散化及类条件概率分布估计方法。给出了以此为基础构成的贝叶斯分类算法。最后，将此方法用于雷达目标的识别。更多还原

【Abstract】 The Bayesian decision theory is widely used in pattem recognition and signal detection. Only when Class-conditional -probability density is known, the theory can be used. A discrete method for stochastic variable (features) space of class-cond itional-probability density and estimation method for class-conditional -probability distribution is proposed. Bayesian classification algorithm based on the method is given. Finally, the mcthods are applied to recognize radar targets.更多还原