Minimum memory for generating rare events.
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[1] James P. Crutchfield,et al. Occam’s Quantum Strop: Synchronizing and Compressing Classical Cryptic Processes via a Quantum Channel , 2015, Scientific Reports.
[2] James P. Crutchfield,et al. Signatures of Infinity: Nonergodicity and Resource Scaling in Prediction, Complexity, and Learning , 2015, Physical review. E, Statistical, nonlinear, and soft matter physics.
[3] Lenard,et al. Statistical Mechanics and Mathematical Problems , 1973 .
[4] B. McMillan. The Basic Theorems of Information Theory , 1953 .
[5] A. Si,et al. Entropy,Large Deviations,and Statistical Mechanics , 2011 .
[6] Richard W Clarke,et al. Application of computational mechanics to the analysis of natural data: an example in geomagnetism. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.
[7] Neri Merhav,et al. On the estimation of the order of a Markov chain and universal data compression , 1989, IEEE Trans. Inf. Theory.
[8] J. Crutchfield. Between order and chaos , 2011, Nature Physics.
[9] Lawrence R. Rabiner,et al. A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.
[10] E. Lorenz,et al. Short term fluctuations of wind and solar power systems , 2016, 1606.03426.
[11] James P Crutchfield,et al. Time's barbed arrow: irreversibility, crypticity, and stored information. , 2009, Physical review letters.
[12] Daniel Ray Upper,et al. Theory and algorithms for hidden Markov models and generalized hidden Markov models , 1998 .
[13] Alexander B. Neiman,et al. Characterizing the dynamics of stochastic bistable systems by measures of complexity , 1997 .
[14] Feller William,et al. An Introduction To Probability Theory And Its Applications , 1950 .
[15] James P. Crutchfield,et al. The Hidden Fragility of Complex Systems— Consequences of Change, Changing Consequences , 2020, 2003.11153.
[16] Y. Tsuji,et al. Similarity scaling of pressure fluctuation in turbulence. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.
[17] W. Marsden. I and J , 2012 .
[18] G. Parmigiani. Large Deviation Techniques in Decision, Simulation and Estimation , 1992 .
[19] Muhammad Sahimi,et al. Turbulencelike behavior of seismic time series. , 2009, Physical review letters.
[20] D. Vere-Jones. Markov Chains , 1972, Nature.
[21] James P. Crutchfield,et al. Computational Mechanics: Pattern and Prediction, Structure and Simplicity , 1999, ArXiv.
[22] Nicholas F. Travers. Bounds on Convergence of Entropy Rate Approximations in Hidden Markov Processes , 2013 .
[23] Wolfgang Löhr. Predictive models and generative complexity , 2012, J. Syst. Sci. Complex..
[24] R. Mazo. On the theory of brownian motion , 1973 .
[25] T. Cover,et al. A sandwich proof of the Shannon-McMillan-Breiman theorem , 1988 .
[26] Muhammad Sahimi,et al. Markov analysis and Kramers-Moyal expansion of nonstationary stochastic processes with application to the fluctuations in the oil price. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[27] G. G. Stokes. "J." , 1890, The New Yale Book of Quotations.
[28] Amir Dembo,et al. Large Deviations Techniques and Applications , 1998 .
[29] Klaus Lehnertz,et al. Stochastic qualifiers of epileptic brain dynamics. , 2007, Physical review letters.
[30] Ji-Ping Huang,et al. Experimental econophysics: Complexity, self-organization, and emergent properties , 2015 .
[31] Cina Aghamohammadi,et al. Permutation approach, high frequency trading and variety of micro patterns in financial time series , 2014 .
[32] DANNY CALEGARI,et al. Thermodynamic Formalism , 2021, Lecture Notes in Mathematics.
[33] James P. Crutchfield,et al. Not All Fluctuations are Created Equal: Spontaneous Variations in Thermodynamic Function , 2016, ArXiv.
[34] R. Durrett. Probability: Theory and Examples , 1993 .
[35] Raymond W. Yeung,et al. Information Theory and Network Coding , 2008 .
[36] S. Varadhan,et al. Large deviations , 2019, Graduate Studies in Mathematics.
[37] Peter Gmeiner,et al. Equality conditions for internal entropies of certain classical and quantum models , 2011, 1108.5303.
[38] Karoline Wiesner,et al. A New Method for Inferring Hidden Markov Models from Noisy Time Sequences , 2012, PloS one.
[39] R. Glen,et al. Identifying and correcting non-Markov states in peptide conformational dynamics. , 2010, The Journal of chemical physics.
[40] Young,et al. Inferring statistical complexity. , 1989, Physical review letters.
[41] S. Varadhan,et al. Asymptotic evaluation of certain Markov process expectations for large time , 1975 .
[42] P. Mazur. On the theory of brownian motion , 1959 .
[43] Thomas M. Cover,et al. Elements of Information Theory , 2005 .
[44] Tamiki Komatsuzaki,et al. Aggregated markov model using time series of single molecule dwell times with minimum excessive information. , 2013, Physical review letters.
[45] Solomon Kullback,et al. Information Theory and Statistics , 1970, The Mathematical Gazette.
[46] J. Peinke,et al. Stochastic analysis of different rough surfaces , 2004 .
[47] J. Crutchfield. The calculi of emergence: computation, dynamics and induction , 1994 .
[48] J. Rogers. Chaos , 1876 .
[49] Nihat Ay,et al. On the Generative Nature of Prediction , 2009, Adv. Complex Syst..
[50] Ludwig Boltzmann,et al. Lectures on Gas Theory , 1964 .
[51] Brian H. Marcus,et al. Analyticity of Entropy Rate of Hidden Markov Chains , 2005, IEEE Transactions on Information Theory.
[52] J. Crutchfield,et al. Fluctuation Spectroscopy , 1993 .
[53] Ryan Tan,et al. Towards quantifying complexity with quantum mechanics , 2014, 1404.6255.
[54] Karoline Wiesner,et al. Quantum mechanics can reduce the complexity of classical models , 2011, Nature Communications.
[55] Ericka Stricklin-Parker,et al. Ann , 2005 .
[56] C. E. SHANNON,et al. A mathematical theory of communication , 1948, MOCO.
[57] D. Vvedensky,et al. Langevin equations for fluctuating surfaces. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.
[58] Philip Sura,et al. Stochastic Analysis of Southern and Pacific Ocean Sea Surface Winds , 2003 .
[59] J. Crutchfield,et al. Regularities unseen, randomness observed: levels of entropy convergence. , 2001, Chaos.
[60] J. Peinke,et al. Stochastic nature of series of waiting times. , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.
[61] M. R. Rahimi Tabar,et al. Scale dependence of the directional relationships between coupled time series , 2013 .
[62] T. Nagatani,et al. Traffic jams induced by fluctuation of a leading car. , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.
[63] L. Breiman. The Individual Ergodic Theorem of Information Theory , 1957 .
[64] James P. Crutchfield,et al. A Closed-Form Shave from Occam's Quantum Razor: Exact Results for Quantum Compression , 2015, ArXiv.
[65] William Feller,et al. An Introduction to Probability Theory and Its Applications , 1967 .
[66] L. Rabiner,et al. An introduction to hidden Markov models , 1986, IEEE ASSP Magazine.
[67] L. Christophorou. Science , 2018, Emerging Dynamics: Science, Energy, Society and Values.
[68] Christopher W. Fairall,et al. Complexity in the atmosphere , 2000, IEEE Trans. Geosci. Remote. Sens..
[69] Tom Kuusela,et al. Stochastic heart-rate model can reveal pathologic cardiac dynamics. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.
[70] H. Touchette. The large deviation approach to statistical mechanics , 2008, 0804.0327.
[71] Yoshitsugu Oono,et al. Large Deviation and Statistical Physics , 1989 .
[72] V. Climenhaga. Markov chains and mixing times , 2013 .
[73] Long-range correlation in cosmic microwave background radiation. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.
[74] R. Stephenson. A and V , 1962, The British journal of ophthalmology.
[75] Mervyn P. Freeman,et al. The application of computational mechanics to the analysis of geomagnetic data , 2001 .
[76] Evgueni A. Haroutunian,et al. Information Theory and Statistics , 2011, International Encyclopedia of Statistical Science.
[77] R. Friedrich,et al. Reconstruction of dynamical equations for traffic flow , 2002 .
[78] Nihat Ay,et al. Non-sufficient Memories That Are Sufficient for Prediction , 2009, Complex.
[79] Dla Polski,et al. EURO , 2004 .
[80] Reynaldo D. Pinto,et al. Inferring statistical complexity in the dripping faucet experiment , 1998 .
[81] James P. Crutchfield,et al. Prediction, Retrodiction, and the Amount of Information Stored in the Present , 2009, ArXiv.
[82] James P. Crutchfield,et al. Extreme Quantum Advantage when Simulating Strongly Coupled Classical Systems , 2016, ArXiv.
[83] Patrick Milan,et al. Kolmogorov spectrum of renewable wind and solar power fluctuations , 2014 .
[84] James P. Crutchfield,et al. The Ambiguity of Simplicity , 2016, ArXiv.