产流误差比例系数的系统响应修正方法

为提高洪水预报的精度以及修正的稳定性,在产流误差动态系统响应曲线修正方法的基础上,提出了产流比例系数的系统响应修正方法。将产流系列按照一定原则分成若干组,假定每组存在系统误差,通过引入一个比例系数来表示,应用系统响应理论,选择适当的参数率定方法确定最优比例系数,进而对时段产流量分组进行修正。将产流误差比例系数的系统响应修正方法应用于滩坑流域,并与产流误差动态系统响应曲线修正方法相比较,结果显示,对于流域的17场历史洪水,二者均能提高洪水预报的精度,但前者的修正效果更好,修正稳定性更强,适用范围更广。

Performance Comparison of DCT and VQ Based Techniques for Iris Recognition

Iris recognition enjoys universality, high degree of uniqueness and moderate user co-operation. This makes iris recognition systems unavoidable in emerging security ＆ authentication mechanisms. An iris recognition system based on vector quantization （VQ） techniques is proposed and its performance is compared with the discrete cosine transform （DCT）. The proposed system does not need any pre-processing and segmentation of the iris. We have tested Linde-Buzo- Gray （LBG）, Kekre＇s proportionate error （KPE） algorithm and Kekre＇s fast codebook generation （KFCG） algorithm for the clustering purpose. Proposed vector quantization based method using KFCG requires 99.99% less computations as that of full 2-dimensional DCT. Further, the KFCG method gives better performance with the accuracy of 89.10% outperforming DCT that gives accuracy around 66.10%.