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Description: Singularity RDK 2.0 boot code
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Size: 1103872 |
Author: nikodimys |
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Description: 基于小波变换的mallat算法，用于检测信号的奇异性，实现励磁涌流的鉴别-Based the wavelet transform mallat algorithm for detection signal singularity inrush current identification
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Size: 1024 |
Author: 李明 |
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Description: W12SC3是美国基于USSAERO程序的超声速机翼设计及分析代码，可用于机翼的整个设计、分析及优化过程。-W12SC3- Supersonic wing design and analysis using source and vortex panel
singularity distributions, based on the USSAERO program by Woodward. W12SC3
combines source and vortex panel singularity distributions forcalculating the linear
theory estimate of the configuration aerodynamics. The user can specify Woodward II
calculations for arbitrary body models or Woodward I calculations for an interference
shell that approximates actual body shape. The Carlson correction for supersonic linear
theory wing calculations is applied at wing control points. If desired, COREL will
produce conical panel pressure data for further processing by W12SC3
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Size: 210944 |
Author: 李喜 |
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Description: Most of the approaches proposed in the literature for singularity detection operate on the fingerprint
orientation image. In the
rest
of
this
section,
the
main
approaches are coarsely classified
and a subsection is dedicated
to each family of algorithms.
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Size: 529408 |
Author: mah |
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Description: Most of the approaches proposed in the literature for singularity detection operate on the fingerprint
orientation image. In the
rest
of
this
section,
the
main
approaches are coarsely classified
and a subsection is dedicated
to each family
Platform: |
Size: 644096 |
Author: mah |
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Description: 介绍了小波二进制变换的基本原理 , 简述了小波变换奇异性和信号突变的关系。 基于小波变换, 给出一种结合3R 准则、 软硬阈值折衷法的奇 异信号小波检测方 法。仿真结果表明此法 既能有效地消除噪 声, 又能较好 保留奇异信号-This paper introduces the basic principle of binary wavelet transform, signal singularity and wavelet transform are briefly discussed the relationship between the mutation. Based on wavelet transform, a combination of 3 r principles, hard and soft threshold eclectic method of different signal wavelet detection method. The simulation results show that this method can effectively eliminate the noise, and can keep the singular signal
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Size: 154624 |
Author: 张力 |
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Description: 一阶差分滤波，采用中心查分公式进行微商计算，具有应对奇点的能力，收敛能力较强。-First-order differential filtering, check points with central derivative formula calculation, with the ability to deal with the singularity of strong convergence capability.
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Size: 3072 |
Author: 奥巴马 |
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Description: 利用此函数可以在最小二乘意义上解决非线性曲线拟合（数据
拟合）问题。也就是说，给定输入数据xdata，以及观测的输出数据ydata，找到系数x，使
得函数F(x，xdata)能够最好的拟合向量值-MLS method not only can be applied for the purpose of curve (or surface) fitting,
but also curve (or surface) interpolation when compactly supported singular weighted
function was used. The effective measure has been applied to eliminate singularity in
MLS interpolation. In addition, the bad fitting or interpolation accuracy near the
boundary was improved.
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Size: 186368 |
Author: wxh |
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Description: 本文研究了多重分形的统计物理方法,以上证综合指数长达四年的一分钟高频数据为研究
对象,计算了实际交易数据的多重分形谱及其特征参数,并确定了权重因子的取值范围。结果表
明奇异指数和相应的谱函数作为多重分形谱的重要参数,一定程度上反映了股指本身的变化范围
和高低价位出现频率的变化,然而谱函数可以预测股市趋势的断言在沪市并不成立。
关键词:统计物理 高频数据 多重分形谱 奇异指数-This paper studies the multifractal statistical physics methods, the Shanghai Composite Index more than four years of high frequency data for the study of one minute
Object, calculated multifractal spectrum and characteristic parameters of the actual transaction data, and determine the weighting factor ranges. Results Table
Ming singularity index and the corresponding spectral function as a multi-fractal spectrum of important parameters, to some extent, reflect the range of variation of the index itself
And the level of price changes in the frequency of appearance, but the spectral function can predict stock market trends assertion does not hold in the Shanghai stock market.
Keywords: Statistical Physics high frequency data multifractal spectrum singularity exponent
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Size: 728064 |
Author: baibai |
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Description: Contourlet变换思想，选用拉普拉斯塔式滤波器结构对图像多分辨率分解来捕捉奇异点。-Contourlet transform thinking, the choice of Laplace tower filter structure for multi-resolution images to capture the singularity exploded.
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Size: 606208 |
Author: D.C |
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Description: When extracting discriminative features multimodal
data, current methods rarely concern the data distribution.
In this paper, we present an assumption that is consistent with
the viewpoint of discrimination, that is, a person’s overall
biometric data should be regarded as one class in the input space,
and his different biometric data can form different Gaussians
distributions, i.e., different subclasses. Hence, we propose a novel
multi-modal feature extraction and recognition approach based
on subclass discriminant analysis (SDA). Specifically, one
person’s different bio-data are treated as different subclasses of
one class, and a transformed space is calculated, where the
difference among subclasses belonging to different persons is
maximized, and the difference within each subclass is minimized.
Then, the obtained multi-modal features are used for
classification. Two solutions are presented to overcome the
singularity problem encountered in calculation, which are using
PCA preprocessing,-When extracting discriminative features multimodal
data, current methods rarely concern the data distribution.
In this paper, we present an assumption that is consistent with
the viewpoint of discrimination, that is, a person’s overall
biometric data should be regarded as one class in the input space,
and his different biometric data can form different Gaussians
distributions, i.e., different subclasses. Hence, we propose a novel
multi-modal feature extraction and recognition approach based
on subclass discriminant analysis (SDA). Specifically, one
person’s different bio-data are treated as different subclasses of
one class, and a transformed space is calculated, where the
difference among subclasses belonging to different persons is
maximized, and the difference within each subclass is minimized.
Then, the obtained multi-modal features are used for
classification. Two solutions are presented to overcome the
singularity problem encountered in calculation, which are using
PCA preprocessing,
Platform: |
Size: 588800 |
Author: avinash trivedi |
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Description: Romberg积分通常要求被积函数在积分区间上没有奇点。-Usually require Romberg integral integrand no singularity in the integral interval.
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Size: 3072 |
Author: 张si |
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Description: 基于TMS320F28335的单相全桥逆变器的单极性SPWM的设计-Basis TMS320F28335 Typical Suspension Bridge Reversing Electrode Singularity Polarity SPWM Design
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Size: 541696 |
Author: 马武强 |
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