Algorithmic classification of noncorrelated binary pattern sequences
نویسندگان
چکیده
The main subject of this paper are binary pattern sequences, that is, sequences the form (−1)#(n,A) where A is a set strings 0s and 1s, #(n,A) denotes total number times patterns from appear in expansion n. sequence said to be noncorrelated if corresponding spectral measure equal Lebesgue measure. We show it possible algorithmically verify given noncorrelated. As an application, we compute there exactly 2272 length ≤4. If restrict our attention do not end with 0, put forward sufficient condition for conjecture also necessary, lengths ≤5.
منابع مشابه
Algorithmic Complexity and Stochastic Properties of Finite Binary Sequences
This paper is a survey of concepts and results related to simple Kolmogorov complexity, prefix complexity and resource-bounded complexity. We also consider a new type of complexity— statistical complexity closely related to mathematical statistics. Unlike other discoverers of algorithmic complexity, A. N. Kolmogorov’s leading motive was developing on its basis a mathematical theory more adequat...
متن کاملAn Algorithmic Approach towards Construction of Long Binary Sequences using Modified Jacobi Sequences
Construction of long low autocorrelation binary sequences (LABS) is a complex process which involves many limitations. LABS have many practical applications. In pulse coding schemes, sequences with low autocorrelation side lobe energies are required to reduce the noise and to increase the capability of radars to detect multiple targets. In literature, numerous techniques were employed to solve ...
متن کاملAn Algorithmic Approach towards Construction of Long Binary Sequences using Modified Jacobi Sequences
Construction of long low autocorrelation binary sequences (LABS) is a complex process which involves many limitations. LABS have many practical applications. In pulse coding schemes, sequences with low autocorrelation side lobe energies are required to reduce the noise and to increase the capability of radars to detect multiple targets. In literature, numerous techniques were employed to solve ...
متن کاملAn ANALYSIS OF TEXTURE CLASSIFICATION: LOCAL BINARY PATTERN
This paper presents a novel approach for texture classification and relevance with generalizing the well-known local binary patterns (LBP).
متن کاملPerformance Analysis of Local Binary Pattern Variants in Texture Classification
-Texture classification is a major issue in image analysis and pattern recognition. A number of methods are proposed in the literature including Local Binary Pattern (LBP). The LBP variant (s) plays an active role to extract texture features for texture classification. These are rotation invariant, noise sensitive or noise insensitive mehods. Each method has its own advantages and disadvantages...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Number Theory
سال: 2021
ISSN: ['0022-314X', '1096-1658']
DOI: https://doi.org/10.1016/j.jnt.2020.10.008