DaubechiesWavelet安瓦尔事件>别了 我爱的中国
The Daubechies wavelets, based on the work of Ingrid Daubechies, are a family of orthogonal wavelets defining a discrete wavelet transform and characterized by a maximal number of vanishing moments for some given support. With each wavelet type of this class, there is a scaling function (called the father wavelet) which generates an orthogonal multiresolution analysis.
Daubechies⼩波，基于Ingrid Daubechies的⼯作，是⼀组定义离散⼩波变换的正交⼩波，并且以给定⽀撑的最⼤消失矩数量为特征。对于此类的每个⼩波类型，都有⼀个尺度函数（称为⽗⼩波），它⽣成正交多分辨率分析。服装人台
In general the Daubechies wavelets are chosen to have the highest number A of vanishing moments, (this does not imply
闸管the best smoothness) for given support width 2A - 1.[1] There are two naming schemes in use, D N using the length or number of taps, and db A referring to the number of vanishing moments. So D4 and db2 are the same wavelet transform.
⼀般来说，对于给定的⽀持宽度2A-1，Daubechies⼩波被选择为具有最⾼数⽬的消失矩A（这并不意味 着最佳平滑度）。[1]在使⽤中有两种命名⽅案，DN使⽤抽头的长度或数量，dbA使⽤消失矩的数量。NTS。因此，D4和DB2是相同的⼩波变换。
Among the 2A−1 possible solutions of the algebraic equations for the moment and orthogonality conditions, the one is chosen whose scaling filter has extremal phase. The wavelet transform is also easy to put into practice using the fast wavelet transform. Daubechies wavelets are widely used in solving a broad range of problems, e.g. self-similarity properties of a signal or fractal problems, signal discontinuities, etc.
在矩和正交性条件下的代数⽅程的2A-1可能解中，选择具有极值相位的尺度滤波器。⼩波变换也易于应⽤于快速⼩波变换。Daubechies⼩波在解决信号⾃相似性、分形问题、信号不连续性等问题中得到了⼴泛的应⽤。 ilife 11
河南省汝州市The Daubechies wavelets are not defined in terms of the resulting scaling and wavelet functions; in fact, they are not possible to write down in closed form. The graphs below are generated using the cascade algorithm, a numeric technique consisting of simply inverse-transforming [1 0 0 0 0 ... ] an appropriate number of times.
Daubechies⼩波不是根据得到的缩放和⼩波函数定义的; 事实上，它们不可能以封闭形式写下来。下
⾯的图是使⽤级联算法⽣成的，这是⼀种由简单的逆变换[1 0 0 0.…适当的次数。
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