By John N. A. Brown (auth.), Ignacio Rojas, Gonzalo Joya, Joan Gabestany (eds.)
This two-volume set LNCS 7902 and 7903 constitutes the refereed court cases of the twelfth overseas Work-Conference on synthetic Neural Networks, IWANN 2013, held in Puerto de los angeles Cruz, Tenerife, Spain, in June 2013. The 116 revised papers have been rigorously reviewed and chosen from various submissions for presentation in volumes. The papers discover sections on mathematical and theoretical equipment in computational intelligence, neurocomputational formulations, studying and edition emulation of cognitive features, bio-inspired platforms and neuro-engineering, complicated themes in computational intelligence and applications
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The visual stimuli are sorted by your limbic system into simultaneous messages for two parts of your brain that react very differently. Your cerebral neocortex begins immediately to compare the movement, size, shape and color pattern of the snake to your database of known movements, sizes, shapes and color patterns. If your neocortex were to talk to itself, it might sound like this: “Woah! A live, moving snake… …Now let’s see, there are red, yellow and black stripes, which means either a harmless milk snake or possibly a deadly coral snake.
From . Indeed, the ELM is not designed to cope with such variables irrelevant to the problem at hand. In this spirit, the OP-ELM proposes a three-steps methodology, shortly described here, to address this issue. Extreme Learning Machine: A Robust Modeling Technique? Yes! Data SLFN Construction using ELM Ranking of the best neurons by LARS Selection of the optimal number of neurons by LOO 21 Model Fig. 2. Illustration of the three OP-ELM steps: the SLFN is first built using the ELM approach (random initialization of internal weights and biases); then a LARS algorithm is used to rank the neurons of the hidden layer; finally the selection of the optimal number of neurons for the OP-ELM model is performed using a Leave-One-Out criterion The idea is to build a wrapper around the original ELM, with a neuron pruning strategy.
1 Computer-Centered Computing Of similar value are the surface modifications of the computer mouse, the desk chair, or the computer keyboard. These small “ergonomic” adjustments do not address the fact that none of these tools are really designed based on human needs and abilities. In fact, these tools are all examples of machines that force humans to enter their world. Please allow me to explain. The computer keyboard is based on the typewriter of the mid-twentieth century, a tool that has a rich history of bad design – at least in terms of human use.