机器学习PPT课件(一).pptVIP

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机器学习PPT课件(一)

Introduction Figure 1 Block diagram representation of nervous system. Figure 2 The pyramidal cell. Figure 3 Structural organization of levels in the brain. Figure 4 Cytoarchitectural map of the cerebral cortex. The different areas are identified by the thickness of their layers and types of cells within them. Some of the key sensory areas are as follows: Motor cortex: motor strip, area 4; premotor area, area 6; frontal eye fields, area 8. Somatosensory cortex: areas 3, 1, and 2. Visual cortex: areas 17, 18, and 19. Auditory cortex: areas 41 and 42. (From A. Brodal, 1981; with permission of Oxford University Press.) Figure 5 Nonlinear model of a neuron, labeled k. Figure 6 Affine transformation produced by the presence of a bias; note that vk = bk at uk = 0. Figure 7 Another nonlinear model of a neuron; wk0 accounts for the bias bk. Figure 8 (a) Threshold function. (b) Sigmoid function for varying slope parameter a. Figure 9 lllustrating basic rules for the construction of signal-flow graphs. Figure 10 Signal-flow graph of a neuron. Figure 11 Architectural graph of a neuron. Figure 12 Signal-flow graph of a single-loop feedback system. Figure 13 (a) Signal-flow graph of a first-order, infinite-duration impulse response (IIR) filter. (b) Feedforward approximation of part (a) of the figure, obtained by truncating Eq. (20). Figure 14 Time response of Fig. 13 for three different values of feedforward weight w. (a) Stable. (b) Linear divergence. (c) Exponential divergence. Figure 15 Feedforward network with a single layer of neurons. Figure 16 Fully connected feedforward network with one hidden layer and one output layer. Figure 17 Recurrent network with no self-feedback loops and no hidden neurons. Figure 18 Recurrent network with hidden neurons. Figure 19 Illustrating the relationship between inner product and Euclidean distance as measures of similarity between patterns. Figure 20 Illustrating the combined use of a receptive fiel

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