21,124 research outputs found
Assume-guarantee verification for probabilistic systems
We present a compositional verification technique for systems that exhibit both probabilistic and nondeterministic behaviour. We adopt an assume- guarantee approach to verification, where both the assumptions made about system components and the guarantees that they provide are regular safety properties, represented by finite automata. Unlike previous proposals for assume-guarantee reasoning about probabilistic systems, our approach does not require that components interact in a fully synchronous fashion. In addition, the compositional verification method is efficient and fully automated, based on a reduction to the problem of multi-objective probabilistic model checking. We present asymmetric and circular assume-guarantee rules, and show how they can be adapted to form quantitative queries, yielding lower and upper bounds on the actual probabilities that a property is satisfied. Our techniques have been implemented and applied to several large case studies, including instances where conventional probabilistic verification is infeasible
A novel spectral estimation method by using periodic nonuniform sampling
In this paper we present a method of estimating power spectrum density of random ergodic signals. The method allows use of arbitrarily low sampling rates to achieve the goal. We compare our method with similar schemes reported in research literature and argue superiority of our approach in terms of its suitability for practical implementations. The most visible difference between our approach and the previously reported ones consists in replacing Poisson additive random sampling with deterministic sampling. Comparing with the approaches based on the Poisson additive random sampling, where theoreticall infinitely large resources are needed to implement them accurately, our approach clearly relies on limited and well defined resources
Optimal periodic sampling sequences for nearly-alias-free digital signal processing
Alias-free DSP (DASP) is a methodology of processing signals digitally inside bandwidths that are wider
than the famous Nyquist limit of half of the sampling requency. DASP is facilitated by suitable combination of nonuniform sampling and appropriate processing algorithms. In this paper we propose a new method of constructing sampling schemes for the needs of DASP. Unlike traditional approaches that rely on randomly selected sampling instants we use deterministic schemes. A method of optimizing such sequences aimed at minimization of aliasing is proposed. The approach is tested numerically in an experiment where an undersampled signal is processed using DASP; first to estimate the signal's spectrum support function and then the spectrum itself. We demonstrate advantages of the proposed approach over those that use random sampling
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Two novel nonlinear companding schemes with iterative receiver to reduce PAPR in multi-carrier modulation systems
Companding transform is an efficient and simple method to reduce the Peak-to-Average Power Ratio (PAPR) for Multi-Carrier Modulation (MCM) systems. But if the MCM signal is only simply operated by inverse companding transform at the receiver, the resultant spectrum may exhibit severe in-band and out-of-band radiation of the distortion components, and considerable peak regrowth by excessive channel noises etc. In order to prevent these problems from occurring, in this paper, two novel nonlinear companding schemes with a iterative receiver are proposed to reduce the PAPR. By transforming the amplitude or power of the original MCM signals into uniform distributed signals, the novel schemes can effectively reduce PAPR for different modulation formats and sub-carrier sizes. Despite moderate complexity increasing at the receiver, but it is especially suitable to be combined with iterative channel estimation. Computer simulation results show that the proposed schemes can offer good system performances without any bandwidth expansion
Timescale Spectra in High Energy Astrophysics
A technique of timescale analysis performed directly in the time domain has
been developed recently. We have applied the technique to studying rapid
variabilities of hard X-rays from neutron star and black hole binaries,
gamma-ray bursts and terrestrial gamma-ray flashes. The results indicate that
the time domain method of spectral analysis is a powerful tool in revealing the
underlying physics in high-energy processes in objects.Comment: 7 pages, 4 figures. Invited talk at the 6th Pacific Rim Conference on
Steller Astrophysic
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