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Fix typo in pcn_discrim.md (#69)
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docs/museum/pcn_discrim.md

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@@ -120,8 +120,8 @@ model generalization ability.)
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In the figure below, we graphically depict what the simulated PCN and its
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corresponding conditional generative model (ancestral projection graph) look like
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(the blue dashed arrow just point outs that the layer `mu1` of the feedforward
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sweep step is used initialize the neuronal activities of `z1` in the
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(the blue dashed arrow just points outs that the layer `mu1` of the feedforward
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sweep step is used to initialize the neuronal activities of `z1` in the
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PCN model's dynamics). Note that `mu1` is $\mu^1_t$, `mu2` is $\mu^2_t$, and
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`mu3` is $\mu^3_t$ while `z^1_t` is $\mathbf{z}^1_t$, `z^2_t` is $\mathbf{z}^2_t$, and
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`z^2_t` is $\mathbf{z}^3_t$ (`z^0_t` is the input layer $\mathbf{z}^0$).

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