By Cheng-Lin Liu, Amir Hussain, Bin Luo, Kay Chen Tan, Yi Zeng, Zhaoxiang Zhang

This ebook constitutes the refereed court cases of the eighth overseas convention on mind encouraged Cognitive structures, BICS 2016, held in Beijing, China, in November 2016. The 32 complete papers offered have been conscientiously reviewed and chosen from forty three submissions. They talk about the rising components and demanding situations, current the cutting-edge of brain-inspired cognitive structures study and functions in various fields via protecting many themes in mind encouraged cognitive structures comparable study together with biologically encouraged platforms, cognitive neuroscience, types awareness, and neural computation.

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Characters given by the decoder and the ground truth (essentially in a onehot form) as the objective function. To speed up the training, the minibatch stochastic gradient descent (SGD) algorithm was adopted. The gradient was computed in sentences, and the AdaDelta algorithm was used to adjust the learning rate [21]. In the training phase, there are no keyword input, so we use the first line as the input to generate the entire poem. 4 Implementation The basic attention model does not naturally work well for Chinese poetry generation.

Patterns of fmri activity dissociate overlapping functional brain areas that respond to biological motion. Neuron 49(6), 815–822 (2006) 17. : Speed skills: measuring the visual speed analyzing properties of primate MT neurons. Nat. Neurosci. 4(5), 526–532 (2001) 18. : Brain areas active during visual perception of biological motion. Neuron 35(6), 1167–1175 (2002) 19. : The dual-loop model and the human mirror neuron system: an exploratory combined fMRI and DTI study of the inferior frontal gyrus.

This work was supported by National Natural Science Foundation of China (61271151, 91520202) and Youth Innovation Promotion Association CAS. References 1. : Estimation of task workload from EEG data: new and current tools and perspectives. In: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 6547–6551. IEEE (2011) 2. : EEG-based vigilance estimation using extreme learning machines. Neurocomputing 102, 135–143 (2013) 3. : Real-time EEG-based emotion recognition and its applications.

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