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8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)

作者： Pesce, Marica Repetti, Audrey Wiaux, Yves Heriot Watt Univ Inst Sensors Signals & Syst Edinburgh EH14 4AS Midlothian Scotland Heriot Watt Univ Dept Actuarial Math & Stat Edinburgh EH14 4AS Midlothian Scotland

ISBN: (数字)9781728155494

ISBN: (纸本)9781728155494

Diffusion Magnetic Resonance Imaging is a state-of-the-art technique that can provide accurate identification of complex neuronal fiber configurations in the human brain. Typical acquisition times are however too long for the clinical application. We propose a method to recover the fiber orientation distribution (FOD) at high spatio-angular resolution via practical kq-space under-sampling patterns that enable both acceleration and super-resolution. The inverse problem for FOD reconstruction is regularized by a structured sparsity prior promoting simultaneously voxelwise sparsity and spatial smoothness of fiber orientations. A convex minimization problem is formulated and solved via a forward-backward algorithm. Real data analysis suggest that high spatio-angular resolution FOD mapping can be achieved from severe kq-space acceleration.

关键词： Diffusion MRI k-space q-space inverse problem forward-backward algorithm

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An adaptive splitting algorithm for the sum of two generalized monotone operators and one cocoercive operator

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FIXED POINT THEORY AND algorithmS FOR SCIENCES AND ENGINEERING 2021年第1期2021卷 1-19页

作者： Dao, Minh N. Phan, Hung M. Federat Univ Australia Sch Engn Informat Technol & Phys Sci Ballarat Vic 3353 Australia Univ Massachusetts Kennedy Coll Sci Dept Math Sci Lowell MA 01854 USA

Splitting algorithms for finding a zero of sum of operators often involve multiple steps which are referred to as forward or backward steps. forward steps are the explicit use of the operators and backward steps involve the operators implicitly via their resolvents. In this paper, we study an adaptive splitting algorithm for finding a zero of the sum of three operators. We assume that two of the operators are generalized monotone and their resolvents are computable, while the other operator is cocoercive but its resolvent is missing or costly to compute. Our splitting algorithm adapts new parameters to the generalized monotonicity of the operators and, at the same time, combines appropriate forward and backward steps to guarantee convergence to a solution of the problem.

关键词： Adaptive Douglas-Rachford algorithm Conically averaged operator Fixed point iterations forward-backward algorithm Three-operator splitting

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Counting Patterns in Degenerated Sequences

Counting Patterns in Degenerated Sequences

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4th International Conference Pattern Recognition in Bioinformatics

作者： Nuel, Gregory Univ Paris 05 MAP5 CNRS 8145 F-75006 Paris France

ISBN: (纸本)9783642040306

Biological sequences like DNA or proteins, are always obtained through a sequencing process which might produce some uncertainty. As a result, such sequences are usually written in a degenerated alphabet where some symbols may correspond to several possible letters (ex: IUPAC DNA alphabet). When counting patterns in such degenerated sequences, the question that naturally arises is: how to deal with degenerated positions ? Since most (usually 99%) of the positions are riot degenerated, it is considered harmless to discard the degenerated positions in order to get an observation, but the exact consequences of such a practice are unclear. In this paper, we introduce a rigorous method to take into account the uncertainty of sequencing for biological sequences (DNA, Proteins). We first, introduce a forward-backward approach to compute the marginal distribution of the constrained sequence and use it both to pet-form a Expectation-Maximization estimation of parameters, as well as deriving a heterogeneous Markov distribution for tire constrained sequence. This distribution is hence used along with known DFA-based pattern approaches to obtain the exact distribution of the pattern count under the constraints. As art illustration, we consider a EST dataset from the EMBL database. Despite the fact that only 1% of the positions in this dataset, are degenerated, we show that riot taking into account, these positions might lead to erroneous observations, further proving the interest of our approach.

关键词： forward-backward algorithm Expectation-Maximization algorithmn Markov chain embedding Deterministic Finite state Automaton

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Joint Iterative Decoding of Spatially Coupled Low-Density Parity-Check Codes for Position Errors in Racetrack Memories

Joint Iterative Decoding of Spatially Coupled Low-Density Pa...

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40th Symposium on Information Theory and Its Applications (SITA)

作者： Shibata, Ryo Hosoya, Gou Yashima, Hiroyuki Tokyo Univ Sci Grad Sch Engn Dept Management Sci Tokyo 1258585 Japan Tokyo Univ Sci Dept Informat & Comp Technol Fac Engn Tokyo 1258585 Japan

Racetrack memory (RM) has attracted much attention. In RM, insertion and deletion (ID) errors occur as a result of an unstable reading process and are called position errors. In this paper, we first define a probabilistic channel model of ID errors in RM with multiple read-heads (RHs). Then, we propose a joint iterative decoding algorithm for spatially coupled low-density parity-check (SC-LDPC) codes over such a channel. We investigate the asymptotic behaviors of SC-LDPC codes under the proposed decoding algorithm using density evolution (DE). With DE, we reveal the relationship between the number of RHs and achievable information rates, along with the iterative decoding thresholds. The results show that increasing the number of RHs provides higher decoding performances, although the proposed decoding algorithm requires each codeword bit to be read only once regardless of the number of RHs. Moreover, we show the performance improvement produced by adjusting the order of the SC-LDPC codeword bits in RM.

关键词： insertion and deletion errors spatially coupled low-density parity-check code forward-backward algorithm iterative decoding

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An Improvement of HSMM-Based Speech Synthesis by Duration-Dependent State Transition Probabilities

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6th International Symposium on Neural Networks

作者： Tao, Jing Liu, Wenju Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing 100190 Peoples R China

ISBN: (纸本)9783642015120

In this paper. we propose all improvement of hidden semi-Markov model (HSMM) based speech synthesis system by duration- dependent state transition probabilities. In traditional HMM algorithm, the probability of the duration of a state decreases exponentially with time, which does not provide,in adequate representation of the temporal Structure of speech. To overcome this limitation, HSMM, which models explicitly the state duration distribution, was proposed. However, there is still in inconsistency. Although HSMM has explicit State duration probability distributions. the state transition probabilities are duration-invariant. In this paper, we introduce duration-dependent state transition probabilities, which are able to characterize the timescale distortion at particular instant of an utterance more effectively. into HSMM based speech synthesis system. Correspondingly we improve forward-backward algorithm and re-derive parameter re-estimation formulae. Experimental results show that the proposed method improves the naturalness of the synthesized speech.

关键词： Speech Synthesis Duration-Dependent State Transition Probabilities forward-backward algorithm

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REGULARIZED FOURIER PTYCHOGRAPHY USING AN ONLINE PLUG-AND-PLAY algorithm 44

REGULARIZED FOURIER PTYCHOGRAPHY USING AN ONLINE PLUG-AND-PL...

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44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Sun, Yu Xu, Shiqi Li, Yunzhe Tian, Lei Wohlberg, Brendt Kamilov, Ulugbek S. Washington Univ Dept Comp Sci & Engn St Louis MO 63130 USA Washington Univ Dept Elect & Syst Engn St Louis MO 63130 USA Boston Univ Dept Elect & Comp Engn Boston MA 02215 USA Los Alamos Natl Lab Div Theoret Los Alamos NM 87545 USA

ISBN: (纸本)9781479981311

The plug-and-play priors (PnP) framework has been recently shown to achieve state-of-the-art results in regularized image reconstruction by leveraging a sophisticated denoiser within an iterative algorithm. In this paper, we propose a new online PnP algorithm for Fourier ptychographic microscopy (FPM) based on the accelerated proximal gradient method (APGM). Specifically, the proposed algorithm uses only a subset of measurements, which makes it scalable to a large set of measurements. We validate the algorithm by showing that it can lead to significant performance gains on both simulated and experimental data.

关键词： Fourier ptychography plug-and-play priors stochastic gradient descent proximal-gradient method forward-backward algorithm nonconvex optimization

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A Maximum Principle for Controlled Time-Symmetric forward-backward Doubly Stochastic Differential Equation with Initial-Terminal Sate Constraints

ABSTRACT AND APPLIED ANALYSIS

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ABSTRACT AND APPLIED ANALYSIS 2012年第Spe11期2012卷 1-29页

作者： Ji, Shaolin Wei, Qingmeng Zhang, Xiumin Shandong Univ Inst Financial Studies Jinan 250100 Shandong Peoples R China Shandong Univ Inst Math Jinan 250100 Shandong Peoples R China

We study the optimal control problem of a controlled time-symmetric forward-backward doubly stochastic differential equation with initial-terminal state constraints. Applying the terminal perturbation method and Ekeland's variation principle, a necessary condition of the stochastic optimal control, that is, stochastic maximum principle, is derived. Applications to backward doubly stochastic linear-quadratic control models are investigated.

关键词： MAXIMUM principles (Mathematics) SYMMETRY (Mathematics) forward-backward algorithm STOCHASTIC differential equations OPTIMAL control theory PERTURBATION (Mathematics) MATHEMATICAL models

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forward-backward multiplicity correlations in relativistic heavy-ion collisions in a superposition approach

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Physical Review C 2013年第4期88卷 044913-044913页

作者： Adam Olszewski Wojciech Broniowski Institute of Physics Jan Kochanowski University PL-25406 Kielce Poland Institut de Physique Théorique CNRS/URA 2306 F-91191 Gif-sur-Yvette France The H. Niewodniczański Institute of Nuclear Physics Polish Academy of Sciences PL-31342 Kraków Poland

We analyze the multiplicity correlations between distant forward and backward rapidity regions in relativistic heavy-ion collisions in a superposition framework, where the particle production occurs through independent emission from correlated sources. This in principle allows for inferring information on the long-range forward-backward correlations of the sources in the earliest phase of the collision, based solely on the experimental information on the statistical features of the observed particle distributions. Our three-stage study incorporates the fluctuations of parton production in the early phase, the effect of intermediate hydrodynamic evolution, as well as fluctuations in the production of particles at freeze-out. We investigate the dependence of the results on the features of the overlaid distributions and hydrodynamics, as well as the centrality dependence. We analyze the existing data from the STAR Collaboration. Predictions for the forward-backward multiplicity correlations in Pb+Pb collisions to be analyzed at the Large Hadron Collider are also made.

关键词： forward-backward algorithm PARTICLES (Nuclear physics) -- Multiplicity CORRELATION (Statistics) RELATIVISTIC Heavy Ion Collider HEAVY ion collisions SUPERPOSITION principle (Physics) LEAD

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forward Tevatron top quarks and backward LHC top quarks with associates

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Physical Review D 2012年第9期86卷 094040-094040页

作者： Jure Drobnak Alexander L. Kagan Jernej F. Kamenik Gilad Perez Jure Zupan Josef Stefan Institute Jamova 39 1000 Ljubljana Slovenia Department of Physics University of Cincinnati Cincinnati Ohio 45221 USA CERN Theoretical Physics CH-1211 Geneva 23 Switzerland Faculty of Mathematics and Physics University of Ljubljana Jadranska 19 1000 Ljubljana Slovenia Department of Particle Physics and Astrophysics Weizmann Institute of Science Rehovot 76100 Israel

The anomalous forward-backward asymmetry (AFB) in tt¯ production at the Tevatron is in apparent contradiction with the tt¯ charge asymmetry (AC) measurements at the LHC, which agree well with the standard model predictions. We argue that associated production of a state with [ut¯] flavor quantum numbers can lead to a sizable negative contribution to AC. Exchange of such a resonance in the t channel would lead to positive contributions to AFB and AC, as has been extensively discussed in the literature. Given the additional negative AC contribution, both the Tevatron and LHC data can be naturally accommodated within this framework. A simple realization of this setup is the well known example of a Z′ with flavor off-diagonal up-top couplings. We provide a detailed study of this model, demonstrating that it indeed reproduces the tt¯ asymmetry data, and is compatible with other constraints, e.g., t+jet resonance searches, tt¯ inclusive jet multiplicities, and atomic parity violation.

关键词： QUARKS LARGE Hadron Collider (France & Switzerland) forward-backward algorithm STANDARD model (Nuclear physics) PREDICTION models QUANTUM theory

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Probabilistic approach to viscosity solutions of the Cauchy problems for systems if fully nonlinear parabolic equations

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Journal of Mathematical Sciences (United States) 2013年第6期188卷 655-672页

作者： Belopolskaya, Ya. I. Woyczynski, W.A. St. Petersburg State University for Architectural and civil Engineering St. Petersburg Russian Federation Case Western Reserve University Cleveland United States

In this paper, we discuss a probabilistic approach to construction of a viscosity solution of the Cauchy problem for a system of nonlinear parabolic equations. Our approach is based on reduction of the original problem to a system of quasilinear parabolic equation in the first step and to a system of fully coupled forward-backward stochastic differential equations in the second step. Solution of the stochastic problem allows us to construct a probabilistic representation of a viscosity solution of the original problem and state conditions which ensure the existence and uniqueness of this solution. © 2013 Springer Science+Business Media New York.

关键词： PROBABILITY theory VISCOSITY solutions CAUCHY problem NONLINEAR equations UNIQUENESS (Mathematics) forward-backward algorithm

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