摘要目的 针对现场可编程门阵列( FPGA)实时系统在体感诱发电位信号检测中的应用，设计一种基于定点数运算的自适应噪声消除器，用于改善体感诱发电位的信噪比。方法对影响定点数算法性能的关键参数进行优化选择，并与基于浮点数运算的自适应噪声消除器的性能进行比较。结果仿真实验表明，定点数自适应噪声消除器的输出与真实体感诱发电位信号之间的失真略大于浮点数算法，选择优化的收敛系数能使定点数算法的结果相当于浮点数算法的结果。结论通过合理的参数选择，基于定点数运算的自适应噪声消除器能够满足实际使用的要求。

abstractsObjective To efficiently detect somsatosensory evoked potential (SEP) using field programmable gate array (FPGA) real-time system, fixed-point algorithm based adaptive noise canceller (ANC) was designed to improve signal to noise ratio (SNR). Methods With the optimization of important parameters that influence the performance of fixed-point algorithm ANC, the performance was compared to that of floating-point algorithm ANC which was isolated from the effect of quantization error. Results In the simulation study, the outputs of fixed-point-based ANC showed a little higher distortion from real SEP signals than that of floating-point algorithm ANC. In the optimal selection of μ value, fixed-point algorithm ANC could get as good results as floating-point algorithm. Conclusion With appropriate parameter values, fixed-point algorithm ANC is able to improve SNR of SEP as well as that of fixed-point algorithm ANC.