网络释义 1. 超高斯函数 超高斯函数,Super-Gaussian... ... ) Super-Gaussian function 超高斯函数 ) super Gaussian spectrum function 超高斯谱函数 ... www.dictall.com|基于1 个网页© 2025 Microsoft 隐私声明和 Cookie 法律声明 广告 帮助 反馈...
We use a higher-order or super-Gaussian function to parameterize the shapes, locations, and orientations of mechanical loads and supports. With a distance function as an input, the super-Gaussian function projects smooth geometric shapes which can be used to model various types of boundary ...
Super-Gaussian light spread function was designed for high dynamic range liquid crystal displays. A dual-liquid-crystal-panel system was constructed to simulate an HDR display, and to evaluate the implementation of the proposed super-Gaussian and a general Gaussian distributions. According to the resu...
The pulse resonance occurs and there is a maximum EPP creation, when the cosine function reaches its maximum value. The resonance condition fulfils (τ + 2t1) E = 2kπ(k = 0, 1, 2...), where E = E p − En is the energy gap between the elec- trons transit from the negative...
(NNLSE),is presented.In the sub-strongly non-local case,an approximate analytical solution is obtained for an arbitrary response function by a variational approach.The solution with a combination of the Jacobian fuction beams width shows that the shift of phase,the spatial chirp and the critical...
Meanwhile, we keep the manual rendering function with a similar usage of the counterpart in3D-GS, one can run it by python render.py -m <path to trained model> # Generate renderings python metrics.py -m <path to trained model> # Compute error metrics on renderings ...
Characterization of the planar structure is achieved through the input impedance function that permit us to reduce the volumetric structure to one single surface. The behavior of supergaussian monochromatic beams under reflection at such surface can be obtained as a function of the film parameters. ...
Meanwhile, we keep the manual rendering function with a similar usage of the counterpart in3D-GS, one can run it by python render.py -m <path to trained model> # Generate renderings python metrics.py -m <path to trained model> # Compute error metrics on renderings ...
However, in the Matlab ® case, an image processing and fit data Toolbox is required for its application. The description laid out in this work can be used to build a simple algorithm and fitting that can be implemented with any suitable known function....
A square exponential kernel function-Gaussian process regression model is used to train the training set and obtain the surrogate model, which is then evaluated using three metrics to assess its accuracy. Finally, genetic algorithm optimization research is conducted on the surrogate model with maximum...