QRS wave starting point end point positioning method based on regularized least square regression learning

A QRS wave starting point end point positioning method based on regularized least square regression learning comprises the following steps: building a series of detection methods, detection criterions and threshold parameters according to function quadrature decomposition idea in the Hilbert space and the regularized least square regression learning algorithm, thus finally detecting the QRS wave and positioning the starting point and end point; carrying out inner product operation on an electrocardiosignal and a gauss function first order derived function so as to obtain an inner product sequence; selecting the reproducing kernel Hilbert space formed by the gauss kernel function as the approximation space of the regularized least square regression learning algorithm; using a real symmetric matrix square root decomposition method solving algorithm to obtain the novel inner product sequence. 种基于正则化最小二乘回归学习的QRS波起点终点定位方法，该方法是：基于函数在Hilbert空间中正交分解的思想结合正则化最小二乘回归学习算法，构建系列检测方法、检测准则和阈值参数，最终检测出QRS波并定位出其起点、终点位置；首先将心电信号与高