Fuzzy Information and Engineering Volume 2 by Rui-rui Zheng, Ji-yin Zhao, Bao-chun Wu (auth.), Bingyuan

By Rui-rui Zheng, Ji-yin Zhao, Bao-chun Wu (auth.), Bingyuan Cao, Tai-Fu Li, Cheng-Yi Zhang (eds.)

This publication is the complaints of the 3rd overseas convention on Fuzzy info and Engineering (ICFIE 2009) held within the recognized mountain urban Chongqing in Southwestern China, from September 26-29, 2009. merely high quality papers are incorporated. The ICFIE 2009, equipped at the luck of prior meetings, the ICFIE 2007 (Guangzhou, China), is an incredible symposium for scientists, engineers and practitioners on the earth to provide their up to date effects, principles, advancements and purposes in all components of fuzzy details and engineering. It goals to bolster family members among learn laboratories and universities, and to create a prime symposium for international scientists in fuzzy fields as follows:

  • Fuzzy Information;
  • Fuzzy units and Systems;
  • Soft Computing;
  • Fuzzy Engineering;
  • Fuzzy Operation learn and Management;
  • Artificial Intelligence;
  • Fuzzy arithmetic and platforms in functions, etc.

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883–888. 10. : Digital Image Processing Using MATLAB. Publishing House of Electronics Industry, Beijing (2004) 11. : Recognition-based handwritten Chinese character segmentation using a probabilistic Viterbi algorithm. cn Abstract. A novel digital image covert communication algorithm is proposed to use the generalized fuzzy c-means clustering (GFCM), human visual system (HVS) and discrete cosine transform (DCT). The original image blocks are classified into two classes based on several characteristic parameters with HVS.

Let ξ = {ξi |i = 1, 2, · · ·N }, s = {si |i = 1, 2, · · ·N }, then the problem of resolving OSH is converted to: 1 M in{ϕ(w, ξ, s)} = w 2 N 2 +C si ξi i=1 yi (wT ϕ(xi ) + b) ≥ 1 − ξi , ξi ≥ 0, i = 1, 2, · · ·, N where, w = (w1 , w2 , · · ·, wN )T . And by LMM, we get the objective function: L(w, α, β) = f (w) − ∗ L(w, b, ξ, α, β) = 1 2 w 2 k i=1 N αi gi (w) − +C i=1 l ξ i si − M axw(x) = i=1 αi − N m j=1 βj hj (w) = αt g(w) − β t h(w) αi (yi (wT φ(xi ) + b) − 1 + ξi ) − i=1 l l 1 αi αj yi yj k(xi , xj ) 2 i=1 j=1 N j=1 βj ξj (7) l where, i=1 yi αi = 0, 0 ≤ αi ≤ si C, i = 1, 2, · · ·, N .

5 Modified New Optimal Rules There are still redundant paths in Fig. 8, two rules are put forward to ulteriorly optimize paths. 1) Rule 4(instead of original rule 4): the first line and the last line of image IIW ×IH are scanned separately. If there are n consecutive paths, and distance between any two neighbor paths of them is less than Tdis , then the path with the smallest t value will be reserved. If these paths have the same t value, remain path is chosen based on its position in image I. The left path will be reserved on condition that all the consecutive paths are on the left side of image I, otherwise the right path will be chosen.

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