Descriptional complexity of iterated uniform finite-state transducers

被引:6
|
作者
Kutrib, Martin [1 ]
Malcher, Andreas [1 ]
Mereghetti, Carlo [2 ]
Palano, Beatrice [3 ]
机构
[1] Univ Giessen, Inst Informat, Arndtstr 2, D-35392 Giessen, Germany
[2] Univ Milan, Dipartimento Fis Aldo Pontremoli, Via Celoria 16, I-20133 Milan, Italy
[3] Univ Milan, Dipartimento Informat Giovanni Degli Antoni, Via Celoria 18, I-20133 Milan, Italy
关键词
Iterated transducers; State complexity; Sweep complexity; Decidability;
D O I
10.1016/j.ic.2021.104691
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
We introduce the deterministic computational model of an iterated uniform finite-state transducer (iufst). An iufst performs the same length-preserving transduction on several left-to-right sweeps. The first sweep acts on the input string, any other sweep processes the output of the previous one. The iufst accepts by halting in an accepting state at the end of a sweep.First, we study constant sweep bounded iufsts. We prove their computational power coincides with the class of regular languages. We show their descriptional power vs. deterministic finite automata, and the state cost of implementing language operations. We prove the NL-completeness of typical decision problems.Next, we analyze non-constant sweep bounded iufsts. We show they can accept non-regular languages provided an at least logarithmic amount of sweeps is allowed. We exhibit a proper non-regular language hierarchy depending on sweep complexity. The non-semidecidability of typical decision problems is also addressed. (c) 2021 Elsevier Inc. All rights reserved.
引用
收藏
页数:17
相关论文
共 50 条
  • [41] STATE-SIZE HIERARCHY FOR FINITE-STATE COMPLEXITY
    Calude, Cristian S.
    Salomaa, Kai
    Roblot, Tania K.
    INTERNATIONAL JOURNAL OF FOUNDATIONS OF COMPUTER SCIENCE, 2012, 23 (01) : 37 - 50
  • [42] THE PARALLEL COMPLEXITY OF FINITE-STATE AUTOMATA PROBLEMS
    SANG, C
    HUYNH, DT
    INFORMATION AND COMPUTATION, 1992, 97 (01) : 1 - 22
  • [43] Descriptional Complexity of (Un)ambiguous Finite State Machines and Pushdown Automata
    Holzer, Markus
    Kutrib, Martin
    REACHABILITY PROBLEMS, 2010, 6227 : 1 - 23
  • [44] Learning finite-state transducers: Evolution versus heuristic state merging
    Lucas, Simon M.
    Reynolds, T. Jeff
    IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2007, 11 (03) : 308 - 325
  • [45] Descriptional and Computational Complexity of Finite Automata
    Holzer, Markus
    Kutrib, Martin
    LANGUAGE AND AUTOMATA THEORY AND APPLICATIONS, 2009, 5457 : 23 - 42
  • [46] Descriptional complexity of nondeterministic finite automata
    Salomaa, Kai
    Developments in Language Theory, Proceedings, 2007, 4588 : 31 - 35
  • [47] Efficient and Robust Music Identification With Weighted Finite-State Transducers
    Mohri, Mehryar
    Moreno, Pedro J.
    Weinstein, Eugene
    IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2010, 18 (01): : 197 - 207
  • [48] Speech-to-speech translation based on finite-state transducers
    Casacuberta, F
    Llorens, D
    Martínez, C
    Molau, S
    Nevado, F
    Ney, H
    Pastor, M
    Picó, D
    Sanchis, A
    Vidal, E
    Vilar, JM
    2001 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS I-VI, PROCEEDINGS: VOL I: SPEECH PROCESSING 1; VOL II: SPEECH PROCESSING 2 IND TECHNOL TRACK DESIGN & IMPLEMENTATION OF SIGNAL PROCESSING SYSTEMS NEURALNETWORKS FOR SIGNAL PROCESSING; VOL III: IMAGE & MULTIDIMENSIONAL SIGNAL PROCESSING MULTIMEDIA SIGNAL PROCESSING, 2001, : 613 - 616
  • [49] KEFST: a knowledge extraction framework using finite-state transducers
    Mahmood, Ahsan
    Khan, Hikmat Ullah
    Rehman, Zahoor Ur
    Iqbal, Khalid
    Faisal, Ch. Muhmmad Shahzad
    ELECTRONIC LIBRARY, 2019, 37 (02): : 365 - 384
  • [50] Speech translation with phrase based stochastic finite-state transducers
    Perez, Alicia
    Ines Torres, M.
    Casacuberta, Francisco
    2007 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL IV, PTS 1-3, 2007, : 113 - +