| 1. | Chapter 3 introduces b - spline smoothed rejection sampling method
第3章提出了b样条光滑拒绝抽样方法。 |
| 2. | Comments on revision technique in cubic b - spline smoothing an inverse diffusion restoration understanding
样条磨光的盈亏修正技术与图象反扩散恢复 |
| 3. | The cubic b - spline smoothing filter operator to perform multi - scale filtering was designed using the characteristics of wavelet transform
摘要利用小波变换的特点，设计了3次b样条平滑滤波算子。 |
| 4. | We use b - spline smoothing technique to smooth the characteristic function without changing the integral quantity and get a differentiable weight function . the method considerably improves the quality of sampling points
我们用b样条磨光技术在不改变积分值的前提下磨光特征函数，用可微的权重函数代替特征函数，提高了采样的质量。 |
| 5. | So the b - spline smoothed rejection sampling method is indirectly proved to be superior to the standard rejection sampling method . chapter 4 is about the monte carlo integration . we get a theoretical error of the fine antithetic variables monte carlo ( famc ) method for multidimensional integration
第4章是关于蒙特卡罗积分的，得出了用于多重积分的精细对偶变数蒙特卡罗( fineantitheticvariablesmontecarlo ，简称famc )方法的误差估计式。 |
| 6. | We apply the b - spline smoothed rejection sampling method to importance sampling . numerical experiments show that the error size o ( n - 1 ) is regained by using the b - spline smoothed rejection method for quasi - monte carlo estimate . the error bound of monte carlo method using b - spline smoothed importance sampling is also better than that of the standard monte carlo method
将b样条光滑拒绝方法用于重要抽样估计，数值例子显示拟蒙特卡罗积分的精度重新达到了o ( n ~ ( - 1 ) )的阶，而对于蒙特卡罗积分，采用b样条光滑重要抽样，其精度也比标准积分的精度o ( n ~ ( - 2 / 1 ) )好。 |
