It integrates the coning , sculling and scrolling corrections all together , simplifying the algorithm structure and implementation complexity . 2 . the new navigation algorithm is analyzed and compared with the conventional one from various aspects 对偶四元数算法将传统算法中的圆锥、划船和卷轴修正整合到一起,大大简化了算法结构,降低了实现难度。
We propose a new method in this papef , which uses the cofltours of two sphere images to realize the orientation . the method overcomes the defect of classical algorithins , which can not realize the orientation if there are no clear textures on the surface of a sphere 我们给出了一种利用球面的两幅图像的轮廓线来实现球体定位的新方法，该方法克服了传统算法中没有明显的纹理就不能实现定位的缺点。
The computer simulation shows that the proposed algorithm is better in both restoration ratio and restoration speed than the existed conventional ones . in the quantity of message during restoration processing , the improved algorithm is also better than the old one 计算机仿真表明，所提改进算法的恢复率和恢复速度都优于传统算法，比改进前的一次函数评估法也有所改善，尤其是在恢复过程中的消息数，得到了进一步的削减。
Combining with the parametric model , proposing an improved global motion estimation algorithm based on the analysis on traditional algorithm . comparing with the traditional algorithm , the experimental results show that the new algorithm is superior in computation and accuracy 结合二维运动场参数模型,在分析现有的全局运动估计算法基础上,提出了改进算法,与传统算法相比,改进算法在计算速度和精确性上都要优于现有算法。
But in many cases , the traditional algorithms are hard to apply , or the application effects are not good . these cases include noisy data , redundant information , incomplete data , and sparse data in database . neural networks can acquire knowledge by training set 本文针对现有数据挖掘方法在很多情况下难以推广应用，例如对于有噪声的数据、有冗余的信息、数据不完整、数据稀疏等情况下，这些传统算法的使用效果往往不佳。
Simulation results showed that the new method can improve the system throughput , obtain higher transmit power utilization and decrease the number of invalid sub - channels without additional complexity when compared with the conventional power allocation algorithm 仿真结果表明，在准静态平坦衰落信道下，与传统算法（如注水算法）相比，新算法能进一步改善系统的吞吐量，提高发射功率的使用效率，减少不可用子信道个数，且无附加复杂度。
This algorithm effectively overcomes the contradictions of traditional algorithm among recognition success rate , recognition time and storage capacity . and this algorithm has been improved notably in aspects of database capacity and real - time , comparing with traditional star pattern recognition algorithm 它有效地解决了传统算法在识别成功率、识别时间与存储量之间的矛盾，并且在数据库容量、实时性等方面较传统星图识别算法有显著改善。
The paper puts forward the clustering algorithm includes : clustering based on grid and iterative , enhanced clustering algorithm base on density and k - medoids , enhanced k - means algorithm ( optimize chooseing consult _ points in iterative process ) , enhanced clustering algorithm base on distance . they can overcome many limitations ( some traditional algorithms terminate in local optimization . many results of cluster are roundness , too many times in partition iterative process ) , which are related to the static architecture of traditional model 在传统聚类算法的基础上,结合我们科学数据挖掘的应用对象?分子动力学数据,提出了迭代网格聚类算法, k -平均和基于密度结合的聚类算法,迭代过程中优化选择中心点的k -平均方法,以及改进型的基于距离的聚类算法等模式识别方法,能够解决传统算法带来的诸多问题(比如一些传统的聚类算法常常收敛于局部最优,发现都模式都趋近于球形,划分方法中迭代次数过多带来的效率问题) 。
According to research of redundant signed digit ( rsd ) calibration theory of pipelined adc , a novel out of range detection rsd technique is provided . when input signal is out of the adc ’ s range , the technique can detect this situation and the wrong output word is avoided 然后,在深入分析冗余位算法的基础上,提出了新型的校正算法,针对传统算法不能判断信号超出adc处理范围的不足,增加了溢出判断功能,既能有效校正比较器的失调,又防止了信号溢出时的误码输出,保证了系统的性能。
This paper considers the ilc from an adaptive control viewpoint . two kinds of new algorithm are proposed for ilc of essential nonlinear systems , which avoid some drawbacks and restricted assumptions of traditional ilc , based on lyapunov stability theory and backstepping technique of nonlinear system 本文利用自适应理论设计迭代学习控制，基于lyapunov稳定性理论，结合本质非线性系统的backstepping设计方法，提出了两类本质非线性系统的迭代学习控制新算法，这些算法克服了传统迭代学习控制的许多缺陷，放松了传统算法的一些限制性假设。
