By John N. A. Brown (auth.), Ignacio Rojas, Gonzalo Joya, Joan Gabestany (eds.)
This two-volume set LNCS 7902 and 7903 constitutes the refereed lawsuits of the twelfth overseas Work-Conference on man made Neural Networks, IWANN 2013, held in Puerto de l. a. Cruz, Tenerife, Spain, in June 2013. The 116 revised papers have been conscientiously reviewed and chosen from a variety of submissions for presentation in volumes. The papers discover sections on mathematical and theoretical equipment in computational intelligence, neurocomputational formulations, studying and version emulation of cognitive services, bio-inspired platforms and neuro-engineering, complicated themes in computational intelligence and applications
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Additional info for Advances in Computational Intelligence: 12th International Work-Conference on Artificial Neural Networks, IWANN 2013, Puerto de la Cruz, Tenerife, Spain, June 12-14, 2013, Proceedings, Part I
The increase in the number of samples can also become problematic, for it leads to increased computational times for model building. The Extreme Learning Machine (ELM) as presented by Huang et al. in  by its very design is fast enough to accommodate such large data sets, where other traditional I. Rojas, G. Joya, and J. ): IWANN 2013, Part I, LNCS 7902, pp. 17–35, 2013. c Springer-Verlag Berlin Heidelberg 2013 18 A. Lendasse et al. machine learning techniques have very large computational times.
Too often, they appear directly over the space at the bottom righthand corner of the monitor where I am typing the last words on a line. I don’t mind not being able to see what I’m typing, but it is well-understood that a written interruption that appears in line-of-sight during a writing task has a catastrophic effect on productivity. It can take up to twenty minutes to regain deep focus after only an unconscious moment of reading the interrupting message. On my computer, the email alert appears as an almost entirely transparent version of the icon my colleague uses to represent herself in our email exchanges.
Furthermore, it requires a peculiar set of very controlled motions based on the position and orientation of the desk, table, tray or other surface one is using. This means that one of two strategies is possible: a) one holds one’s arm in the air, pushing the mouse around in a state of constant dynamic tension and using the large muscles of the shoulder and elbow joints to execute precise movements, or, b) one rests one’s arm on an available surface and performs the steering action with the distal segments of the upper limb.
Advances in Computational Intelligence: 12th International Work-Conference on Artificial Neural Networks, IWANN 2013, Puerto de la Cruz, Tenerife, Spain, June 12-14, 2013, Proceedings, Part I by John N. A. Brown (auth.), Ignacio Rojas, Gonzalo Joya, Joan Gabestany (eds.)