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perceptron
感知器感知器算法训练二元线性分类器。结构体数据使用感知器学习规则
找到给定的二分类标签数据超平面。
(PERCEPTRON Perceptron algorithm to train binary linear classifier.
Synopsis:
model = perceptron(data)
model = perceptron(data,options)
model = perceptron(data,options,init_model)
Description:
model = perceptron(data) uses the Perceptron learning rule
to find separating hyperplane from given binary labeled data.
model = perceptron(data,options) specifies stopping condition of
the algorithm in structure options:
.tmax [1x1]... maximal number of iterations.
If tmax==-1 then it only returns index (model.last_update)
of data vector which should be used by the algorithm for updating
the linear rule in the next iteration.
model = perceptron(data,options,init_model) specifies initial model
which must contain:
.W [dim x 1] ... normal vector.
.b [1x1] ... bias of hyperplane.
.t [1x1] (optional) ... iteration number.
Input:
data [struct] Labeled (binary) training data.
.X [dim x num)
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1
说明： 一些自己编写的图像插值算法程序。包括最近邻插值，双线性插值和双三次插值(-Recently, the field of bilinear interpolation and interpolation matlab source, comparing the effects of two algorithms.)
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