# Neural networks

22 cards

Undergraduate level engineering course in neural networks. Flash cards to help for revision, et cetera.

Created Aug 6, 2011
by
niibruce

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 Side A Side B 1 Name two neural network topologies Feed forward topology (data flow is in the forward direction only; no feedback) and Recurrent... 2 Examples of feed forward networks The perceptron and adaline 3 What is supervised learning? Training by providing an input/output set and using the actual output of the network to calculate... 4 What is unsupervised learning? a kind of learning where the system is trained to discover statistically salient features of... 5 what is adaptive resonance theory? no idea... 6 What is neural computing? Neural computing is the study of networks of adaptable units which, through a process oflearning... 7 formal definition of the associative memory problem store a set of k patterns such that when presented with a new pattern Pi the network... 8 Stability criterion for associative networks The network enters a state where for all j the sign of wjxij = the sign... 9 What property relating to errors do we require of neural networks Insensitivity to small errors in the input pattern. 10 What are attractors? These are stored patterns in the configuration space and they attract the network to one of... 11 State Oja's rule for unsupervised learning It's based on Hebbian learning, which states that the weights are modified by a term proportional... 12 In unsupervised, competitive learning what determines the winning unit? *hint: grandmother... The unit with the largest net input is the winner 13 In Oja's rule what's the limiting term and what does it do? The limiting term is rV2wj. This ensures that |wj| is <=... 14 state the competitive learning rule change in weight = r(input - weight of winning input) 15 state the Kohonen learning rule for neural networks change in weight = r * NF(i, i*)(xj - wij ) for all ijNF =... 16 State the differences between the Kohonen rule and the competitive learning rule With the competitive rule only the inputs to the winning units are updated but with the... 17 Name the condition for the strengthning of synaptic connection between two cells This occurs when both cells are simulstaneously activated. 18 what's the significance of the cost function? it determines the proximity of the output of the network to the desired state. 19 what's the derivative of the sigmoid function? image 20 what is the derivative of the tanh(beta*h) function image 21 for MLPs and backprop and perhaps simple perceptrons how is the change in the weights determined? determined by the partial differential of the cost function with respect to the weight vector. 22 for MCPs the new weight equals..? weight_new = weight_old + change

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