针对多个特征指标的多传感器数据融合问题，将Fisher理论和多数投票法相结合进行数据融合来增加识别率。该方法首先通过Fisher理论得到多个判别函数，然后通过多数投票法继续对得到的判别进行分类得到最后的识别决策。该方法适合多个特征目标识别，计算简单。易于实现-Indicators for multiple features multi-sensor data fusion problem, Fisher majority vote of the Combination of theory and

感知器算法是一种非监督的代数界面分类方法，算法结构简单，但对于团状数据，分类效果理想。-Algebraic classification sensor interface is an unsupervised algorithm, the algorithm is simple in structure, but for groups like the data, the ideal classification.

虚拟力的无线传感网络覆盖，可以实现模式识别领域的数据的分类及回归，欢迎大家下载学习。- Virtual power wireless sensor network coverage, You can achieve data classification and regression pattern recognition, Welcome to download the study.