Advanced Intelligent Computing Theories and Applications. by Daowen Qiu (auth.), De-Shuang Huang, Donald C. Wunsch II,

By Daowen Qiu (auth.), De-Shuang Huang, Donald C. Wunsch II, Daniel S. Levine, Kang-Hyun Jo (eds.)

This ebook - at the side of the 2 volumes CCIS 0015 and LNAI 5226 - constitutes the refereed complaints of the 4th foreign convention on clever Computing, ICIC 2008, held in Shanghai, China, in September 2008.

The 152 revised complete papers of this quantity have been rigorously reviewed and chosen from a complete of 2336 submissions. The papers are equipped in topical sections on organic and quantum computing, clever computing in bioinformatics, computational genomics and proteomics, clever computing in sign processing, clever computing in trend reputation, clever computing in verbal exchange, clever agent and net purposes, clever fault analysis, clever regulate and automation, clever info fusion and safety, clever prediction and time sequence research, typical language processing and specialist platforms, clever image/document retrievals, network-based intelligence and automation, clever robotic platforms in line with imaginative and prescient know-how, and computational intelligence for snapshot analysis.

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Similar to Theorem 1, we can obtain the union operation of 2qcfa’s. Theorem 2. If L1 ∈ 2QCF A 1 (poly − time) and L2 ∈ 2QCF A 2 (poly − time) for 1 , 2 ≥ 0, then L1 ∪ L2 ∈ 2QCF A (poly − time) with = 1 + 2 − 1 2 . Proof. See [18]. 6 D. Qiu By means of the proof of Theorem 2, we also have the following corollary. Corollary 3. If languages L1 and L2 are recognized by 2qcfa’s M1 and M2 with one-sided error probabilities 1 , 2 ∈ [0, 12 ) in polynomial time, respectively, then there exists 2qcfa M such that L1 ∪ L2 is recognized by 2qcfa M with error probability at most 1 + 2 − 1 2 in polynomial time, that is, for any input string x, (i) if x ∈ L1 , then M accepts x with certainty; (ii) if x ∈ L1 , but x ∈ L2 , then M accepts x with probability at least 1 − 1 ; (iii) if x ∈ L1 and x ∈ L2 , then M rejects x with probability at least (1 − 1 )(1 − 2 ).

If it is accepted, then x is also accepted; otherwise, x is rejected. Remark 2. For k ∈ N, let Leq (k, a) = {akn bn |n ∈ N}. Obviously, Leq (1, a) = Leq . Then, by means of the 2qcfa Meq , Leq (k, a) can be recognized by some 2qcfa, denoted by Meq (k, a), with one-sided error probability in polynomial time. √ Indeed, Meq (k, a) is derived from Meq by replacing Uβ with Uβk , where βk = 2kπ. Likewise, denote Leq (k, b) = {bkn an |n ∈ N}. Then Leq (k, b) can be recognized by some 2qcfa Meq (k, b) with one-sided error probability in polynomial time.

The Viterbi algorithm forms a subset of information theory, and has been extensively used in a wide range of applications. The Viterbi algorithm is a maximum-likelihood decoder (which is a maximum-likelihood sequence estimator) and is optimum for a noise type which is statistically characterized as an Additive White Gaussian Noise (AWGN). 2 Quantum Computing Quantum computing (QC) is a method of computation that uses a dynamic process governed by the Schrödinger Equation (SE) [1,3]. 626⋅10-34 J⋅s), V(x,t) is the potential, m is particle’s mass, i is the imaginary number, ψ ( x, t ) is the quantum state, H is the Hamiltonian operator (H = - [(h/2π)2/2m]∇2 + V), and ∇2 is the Laplacian operator.

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