最速下降法
说明: 最速下降法是迭代法的一种,可以用于求解最小二乘问题(线性和非线性都可以)。在求解机器学习算法的模型参数,即无约束优化问题时,梯度下降(Gradient Descent)是最常采用的方法之一,另一种常用的方法是最小二乘法。在求解损失函数的最小值时,可以通过梯度下降法来一步步的迭代求解,得到最小化的损失函数和模型参数值。反过来,如果我们需要求解损失函数的最大值,这时就需要用梯度上升法来迭代了。在机器学习中,基于基本的梯度下降法发展了两种梯度下降方法,分别为随机梯度下降法和批量梯度下降法。(The steepest descent method is a kind of iterative method, which can be used to solve the least squares problem (both linear and nonlinear). In solving the model parameters of machine learning algorithm, that is, unconstrained optimization, gradient descent is one of the most commonly used methods, and the other is the least square method. When solving the minimum value of loss function, the gradient descent method can be used step by step to get the minimum value of loss function and model parameters. Conversely, if we need to solve the maximum value of the loss function, then we need to use the gradient rise method to iterate. In machine learning, two kinds of ladders are developed based on the basic gradient descent method)
- 2019-11-24 13:06:03下载
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产生右图所示图像f1(m,n),其中图像大小为256×256,中间亮条为128
×32,暗处=0,亮处=100。对其进行FFT:
① 同屏显示原图f1(m,n)和FFT(f1)的幅度谱图;
② 若令f2(m,n)=(-1)m+n f1(m,n),重复以上过程,比较二者幅度
谱的异同,简述理由;
③ 若将f2(m,n)顺时针旋转90 度得到f3(m,n),试显示FFT(f3)的幅
度谱,并与FFT(f2)的幅度谱进行比较;
④ 若将f1(m,n) 顺时针旋转90 度得到f4(m,n),令f5(m,n)=f1(m,n)+f4(m,n),试显
示FFT(f5)的幅度谱,并指出其与FFT(f1)和FFT(f4)的关系;
⑤ 若令f6(m,n)=f2(m,n)+f3(m,n),试显示FFT(f6)的幅度谱,并指出其与FFT(f2)和
FFT(f3)的关系,比较FFT(f6)和FFT(f5)的幅度谱。(Generating an image f1 (m, n) shown in the figure, wherein the image size is 256 256, the intermediate light bar 128 32 0 = dark, bright Department 100. Its FFT: ① screen display picture f1 (m, n) and the FFT (f1) of the amplitude spectrum ② If so f2 (m, n) = (-1) m+n f1 (m, n), repeat The above process, comparing the amplitude spectrum of the similarities and differences between the two, brief reasons ③ If f2 (m, n) 90 degrees clockwise to get f3 (m, n), try to display FFT (f3) the amplitude spectrum and with the FFT (f2) comparing the amplitude spectrum ④ If f1 (m, n) obtained by 90 degrees clockwise f4 (m, n), so f5 (m, n) = f1 (m, n)+f4 (m, n ), try to display FFT (f5) amplitude spectrum, and pointed out its relationship with the FFT (f1) and FFT (f4) of ⑤ If so f6 (m, n) = f2 (m, n)+f3 (m, n) and try to display the FFT (f6) amplitude spectrum, and pointed out its relationship with the FFT (f2) and FFT (f3), comparing FFT (f6) and FFT (f5) amplitude spectrum.)
- 2013-11-26 16:24:18下载
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