- Research
- Open Access
Logical entropy of dynamical systems in product MV-algebras and general scheme
- Dagmar Markechová^{1}Email author and
- Beloslav Riečan^{2, 3}
https://doi.org/10.1186/s13662-019-1946-2
© The Author(s) 2019
- Received: 20 June 2018
- Accepted: 2 January 2019
- Published: 14 January 2019
Abstract
The present paper is aimed at studying the entropy of dynamical systems in product MV-algebras. First, by using the concept of logical entropy of a partition in a product MV-algebra introduced and studied by Markechová et al. (Entropy 20:129, 2018), we define the logical entropy of a dynamical system in the studied algebraic structure. In addition, we introduce a general type of entropy of a product MV-algebra dynamical system that includes the logical entropy and the Kolmogorov–Sinai entropy as special cases. It is proved that the proposed entropy measure is invariant under isomorphism of product MV-algebra dynamical systems.
Keywords
- Product MV-algebra
- Partition
- Sub-additive generator
- Entropy
- Dynamical system
MSC
- 28AXX
- 37A35
- 54C70
1 Introduction
Actually, all of the above-mentioned studies are possible in the Kolmogorov probability theory based on the modern integration theory. It gives a possibility to describe and study some problems of uncertainty. Of course, in 1965, Zadeh presented another approach to uncertainty in his article [18]. While the Kolmogorov probability applications are based on objective measurements, the Zadeh fuzzy theory is based on subjective improvements. Of course, one of the first Zadeh articles on the fuzzy set theory was devoted to probability on fuzzy sets (cf. [19]). Therefore, the entropy of fuzzy dynamical systems has also been studied (cf. [20–23]). Recall that the fuzzy set is a mapping \(f:\varOmega \to [ 0, 1 ]\) (\(f(\omega )\) is interpreted as the degree of the element \(\omega \in \varOmega\) to the considered fuzzy set f), hence the fuzzy partition of Ω is a family of fuzzy sets \(A = \{ f_{1},f_{2},\ldots,f_{n} \}\) such that \(\sum_{i = 1}^{n} f_{i} = 1\). And again we can meet the Shannon formula: \(H(A) = - \sum_{i = 1}^{n} p_{i}\log p_{i}\), where \(p_{i} = \int_{\varOmega} f_{i} \,dP\) (cf. [23]). An overview of publications devoted to the entropy of fuzzy dynamical systems can be found in [24].
In [25], Atanassov presented a remarkable generalization of fuzzy sets, i.e., intuitionistic fuzzy sets. An intuitionistic fuzzy set is a pair \(A = (f_{A}, g_{A})\) of fuzzy sets such that \(f_{A} + g_{A} \le 1\). Here \(f_{A}\) is a membership function, \(g_{A}\) a non-membership function. If f is a fuzzy set, then the pair (\(f, 1 - f\)) is an intuitionistic fuzzy set. Also, the probability on families of intuitionistic fuzzy sets has been studied (cf. [26]).
Anyway, the most useful instrument for describing multivalued processes is an MV-algebra [27], especially after its Mundici’s characterization as an interval in a lattice ordered group (cf. [28]). This algebraic structure is currently being studied by many researchers and it is natural that there are many results also regarding entropy in this structure; we refer, for instance, to [29, 30]. A probability theory was studied on MV-algebras as well; for a review, see [31]. Of course, in some problems of probability it is necessary to introduce a product on an MV-algebra, an operation outside the corresponding group addition. The operation of a product on an MV-algebra was introduced independently by Riečan [32] from the point of view of probability and by Montagna [33] from the point of view of mathematical logic. Also, the approach from the point of view of a general algebra proposed by Jakubík in [34] seems to be interesting; see also [35]. We note that the notion of product MV-algebra generalizes some families of fuzzy sets; an example of product MV-algebra is a full tribe of fuzzy sets (see, e.g., [24]).
A suitable entropy theory of Shannon and Kolmogorov–Sinai type for the product MV-algebras has been provided by Petrovičová in [36, 37]. We remark that in our article [38], based on the results of Petrovičová, we introduced the notions of Kullback–Leibler divergence and mutual information of partitions in a product MV-algebra. The logical entropy, the logical divergence, and the logical mutual information of partitions in a product MV-algebra were studied in [1]. In the present paper, we extend the study of logical entropy of partitions in product MV-algebras to the case of product MV-algebra dynamical systems. Moreover, we introduce a general type of entropy of a dynamical system in a product MV-algebra. The proposed definition is based on the concept of the sub-additive generator φ introduced by the authors in [39].
The rest of the article is organized as follows. Section 2 contains basic definitions, notations, and some known facts that will be used in the paper. Our results are presented in the succeeding two sections. In Sect. 3, we define and study the logical entropy of a dynamical system in a product MV-algebra and examine its properties. In Sect. 4, a general type of entropy of a dynamical system in a product MV-algebra is introduced. It is proved that the proposed entropy measure is invariant under isomorphism of product MV-algebra dynamical systems. It is shown that the logical entropy and the Kolmogorov–Sinai entropy of a dynamical system in a product MV-algebra can be obtained as special cases of the proposed general scheme. It follows that the isomorphic product MV-algebra dynamical systems have the same logical entropy and the same Kolmogorov–Sinai entropy. We illustrate the results with examples. Finally, the last section provides brief closing remarks.
2 Basic definitions and related works
3 The logical entropy of dynamical systems in product MV-algebras
In this section, we extend the definition of logical entropy of a partition in a product MV-algebra to the case of dynamical systems and prove basic properties of this measure of information. The known Kolmogorov–Sinai theorem on generators is a useful instrument to compute the entropy of a dynamical system. In the final part of this section we provide a logical version of this theorem for the studied case of product MV-algebra.
Definition 3.1
([37])
- (i)
if \(x + y \le u\), then \(U(x) + U(y) \le u\) and \(U(x + y) = U(x) + U(y)\);
- (ii)
\(U(x \cdot y) = U(x) \cdot U(y)\);
- (iii)
\(\mu (U (x)) = \mu (x)\).
Remark 3.1
For the sake of brevity, we say also a product MV-algebra dynamical system instead of a dynamical system in a product MV-algebra.
Example 3.1
Let (\(\varOmega, S, P, T\)) be a classical dynamical system. Put \(A = \{ \chi_{B}; B \in S \}\), where \(\chi_{B}:\varOmega \to \{ 0, 1 \}\) is the characteristic function of the set \(B \in S\). The family A is closed under the product of characteristic functions, and it is a special case of product MV-algebras. If we define the mapping \(\mu:A \to [0, 1]\) by \(\mu (\chi_{B}) = P(B), B \in S\), then μ is a state on the product MV-algebra \((A, \cdot )\). In addition, let us define the mapping \(U:A \to A\) by the equality \(U(\chi_{B}) = \chi_{B} \circ T = \chi_{T^{ - 1}(B)}, \chi_{B} \in A\). Then the system (\(A, \mu, U \)) is a dynamical system in the considered product MV-algebra \((A, \cdot )\). A measurable partition \(\mathcal{B}= \{ B_{1},B_{2},\ldots,B_{n} \}\) of Ω can be considered as a partition in the product MV-algebra \((A, \cdot )\); it suffices to consider \(\chi_{B_{i}}\) instead of \(B_{i}\).
Example 3.2
Let (\(\varOmega, S, P, T\)) be a classical dynamical system. Let A be a family of all S-measurable functions \(f:\varOmega \to [0, 1]\),the so-called full tribe of fuzzy sets (cf. [24]). The family A is closed also with respect to the natural product of fuzzy sets, and it is an important case of product MV-algebras. If we define the state \(\mu:A \to [0, 1]\) by the equality \(\mu (f) = \int_{\varOmega} f \,dP\) for any element f of A, and the mapping \(U:A \to A\) by the equality \(U(f) = f \circ T, f \in A\), then it is easy to verify that the system (\(A, \mu, U \)) is a dynamical system in the considered product MV-algebra \((A, \cdot )\). The notion of a partition in the product MV-algebra (\(A, \cdot \)) coincides with the notion of a fuzzy partition.
Let (\(A, \mu, U \)) be a dynamical system in a product MV-algebra \((A, \cdot )\), and \(X = (x_{1},x_{2},\ldots,x_{n})\) be a partition in \((A, \cdot )\). Put \(U(X) = (U(x_{1}),U(x_{2}),\ldots,U(x_{n}))\). Since \(x_{1} + x_{2} +\cdots + x_{n} = u\), according to Definition 3.1, we have \(U(x_{1}) + U(x_{2}) +\cdots + U(x_{n}) = U(x_{1} + x_{2} +\cdots + x_{n}) = U(u) = u\), which means that \(U(X)\) is also a partition in \((A, \cdot )\).
Proposition 3.1
- (i)
\(U(X \vee Y) = U(X) \vee U(Y)\);
- (ii)
\(Y \succ X\) implies \(U(Y) \succ U(X)\).
Proof
However, this means that \(U(Y) \succ U(X)\). □
Define \(U^{2} = U \circ U\), and put \(U^{k} = U \circ U^{k - 1}\) for \(k = 1,2,\ldots\) , where \(U^{0}\) is the identical mapping. It is obvious that the map \(U^{k}:A \to A\) satisfies the conditions from Definition 3.1. Hence, for any non-negative integer k, the system (\(A, \mu, U^{k} \)) is a dynamical system in a product MV-algebra \((A, \cdot )\).
Theorem 3.1
- (i)
\(H_{{l}}^{\mu} (U^{k}(X)) = H_{{l}}^{\mu} (X)\);
- (ii)
\(H_{{l}}^{\mu} (U^{k}(X)/U^{k}(Y)) = H_{{l}}^{\mu} (X/Y)\).
Proof
Suppose that \(X = (x_{1},x_{2},\ldots,x_{n})\) and \(Y = (y_{1},y_{2},\ldots,y_{m})\).
Theorem 3.2
Proof
In conclusion, the statement holds by the principle of mathematical induction. □
In the following, we will define the logical entropy of a dynamical system \((A, \mu, U )\). First, we define the logical entropy of U relative to a partition X in \((A, \cdot )\). Then we remove the dependence on X to get the logical entropy of a dynamical system \((A, \mu, U )\). We will need the following proposition.
Proposition 3.2
Proof
This property guarantees (in view of Theorem 4.9, [48]) the existence of \(\lim_{n \to \infty} \frac{1}{n}c_{n}\). □
Definition 3.2
Remark 3.2
Consider any dynamical system (\(A, \mu, U \)) in a product MV-algebra \((A, \cdot )\). If we put \(E = (u)\), then E is a partition in (\(A, \cdot \)) such that \(X \succ E\) for any partition X in \((A, \cdot )\), and with the logical entropy \(H_{l}^{\mu} (E) = 0\). Evidently, \(\bigvee_{k = 0}^{n - 1}U^{k}(E) = E\), hence \(H_{{l}}^{\mu} (U, E) = 0\).
Theorem 3.3
Proof
Theorem 3.4
Let (\(A, \mu, U \)) be a dynamical system in a product MV-algebra \((A, \cdot )\), and \(X, Y\) be partitions in (\(A, \cdot \)) such that \(Y \succ X\). Then \(H_{{l}}^{\mu} (U, X) \le H_{{l}}^{\mu} (U, Y)\).
Proof
Consequently, dividing by n and letting \(n \to \infty\), we get \(H_{{l}}^{\mu} (U, X) \le H_{{l}}^{\mu} (U, Y)\). □
Definition 3.3
Theorem 3.5
Let (\(A, \mu, U \)) be a dynamical system in a product MV-algebra \((A, \cdot )\). Then, for every natural number k, it holds \(H_{{l}}^{\mu} (U^{k}) = k \cdot H_{{l}}^{\mu} (U)\).
Proof
In the rest of this section, we formulate a version of the Kolmogorov–Sinai theorem on generators for the case of the logical entropy of a dynamical system \((A, \mu, U )\).
Definition 3.4
Let (\(A, \mu, U \)) be a dynamical system in a product MV-algebra \((A, \cdot )\). A partition Z in (\(A, \cdot \)) is said to be a generator of a dynamical system (\(A, \mu, U \)) if to any partition X in (\(A, \cdot \)) there exists an integer \(k > 0\) such that \(\bigvee_{i = 0}^{k}U^{i}(Z) \succ X\).
Theorem 3.6
Let Z be a generator of a dynamical system \((A, \mu, U )\). Then \(H_{{l}}^{\mu} (U) = H_{{l}}^{\mu} (U, Z)\).
Proof
4 General type of entropy of dynamical systems in product MV-algebras
In this section, we introduce, based on the function \(\varphi:[0, 1] \to \mathbb{R}\), a general type of entropy of a partition in a product MV-algebra (\(A, \cdot \)) that contains the Shannon entropy and the logical entropy of a partition in a product MV-algebra (\(A, \cdot \)) as special cases. Subsequently, using the concept of φ-entropy of a partition in \((A, \cdot )\), where φ is a so-called sub-additive generator [39], we define a general type of entropy of a dynamical system \((A, \mu, U )\), so-called φ-entropy of a dynamical system \((A, \mu, U )\). We construct for the proposed entropy measure an isomorphism theory of the Kolmogorov–Sinai type.
Definition 4.1
Example 4.1
If we put \(\varphi = s\), where \(s: [ 0, 1 ] \to [ 0, \infty )\) is the Shannon entropy function defined by Eq. (1.1), then we obtain the Shannon entropy of X, and putting \(\varphi = l\), where \(l: [ 0, 1 ] \to [ 0, \infty )\) is the logical entropy function defined by Eq. (1.2), the logical entropy of X is obtained.
Definition 4.2
([39])
Remark 4.1
Remark 4.2
Consider any product MV-algebra (\(A, \cdot \)) and the partition \(E = (u)\) in \((A, \cdot )\). If \(\varphi:[0, 1] \to \mathbb{R}\) is a function with the property that \(\varphi (1) = 0\) (it is evident that all of the above three entropy functions satisfy this condition), then \(H_{\varphi}^{\mu} (E) = 0\).
Theorem 4.1
Proof
To illustrate the result of the previous theorem, we provide the following example.
Example 4.2
Consider the measurable space \(([0, 1], B )\), where B is the σ-algebra of all Borel subsets of the unit interval \([0, 1]\). Let A be a family of all Borel measurable functions \(f: [0, 1] \to [0, 1]\). If we define in the family A the operation⋅ as the natural product of fuzzy sets, then the system (\(A, \cdot \)) is a product MV-algebra. We define a state \(\mu:A \to [0, 1]\) by the equality \(\mu (f) = \int_{0}^{1} f(x)\,dx\) for any element f of A. It is easy to see that the pairs \(X = ( f_{1}, f_{2} ), Y = ( g_{1}, g_{2} )\), where \(f_{1}(x) = x, f_{2}(x) = 1 - x, g_{1}(x) = x^{2}, g_{2}(x) = 1 - x^{2}, x \in [0, 1]\), are two partitions in (\(A, \cdot \)) with the state values \(\frac{1}{2}, \frac{1}{2}\) and \(\frac{1}{3}, \frac{2}{3}\) of the corresponding elements, respectively. The join of partitions X and Y is the system \(X \vee Y = ( f_{1} \cdot g_{1}, f_{1} \cdot g_{2}, f_{2} \cdot g_{1}, f_{2} \cdot g_{2} )\) with the state values \(\frac{1}{4}, \frac{1}{4},\frac{1}{12},\frac{5}{12}\) of the corresponding elements. By simple calculations we get the Shannon entropies \(H_{s}^{\mu} (X) = 1, H_{s}^{\mu} (Y)\mathbin{\dot{ =} }0.9183, H_{s}^{\mu} (X \vee Y)\mathbin{\dot{ =}} 1.8250\); the logical entropies \(H_{l}^{\mu} (X) = 0.5, H_{l}^{\mu} (Y)\mathbin{\dot{ =}} 0.4444, H_{l}^{\mu} (X \vee Y)\mathbin{\dot{ =}} 0.6944\); and the quadratic logical entropies \(H_{k}^{\mu} (X) = 0.75, H_{k}^{\mu} (Y)\mathbin{\dot{ =}} 0.6666, H_{k}^{\mu} (X \vee Y)\mathbin{\dot{ =}} 0.6615\). It is easy to see that for the sub-additive generators \(\varphi = s, \varphi = l\), and \(\varphi = k\), it holds \(H_{\varphi}^{\mu} ( X \vee Y ) \le H_{\varphi}^{\mu} ( X ) + H_{\varphi}^{\mu} ( Y )\), which is consistent with the claim of the previous theorem.
Theorem 4.2
Proof
The statement follows immediately from condition (iii) of Definition 3.1. □
Proposition 4.1
Proof
In view of sub-additivity of φ-entropy (Theorem 4.1) and the previous theorem, the proof can be made similarly as the proof of Proposition 3.2. □
Definition 4.3
Example 4.3
It is clear that putting \(\varphi = l\), where \(l: [ 0, 1 ] \to [ 0, \infty )\) is the logical entropy function defined by Eq. (1.2), we obtain the logical entropy of a dynamical system \((A, \mu, U )\). If we put \(\varphi = s\), where \(s: [ 0, 1 ] \to [ 0, \infty )\) is the Shannon entropy function defined by Eq. (1.1), we obtain the Kolmogorov–Sinai entropy of a dynamical system (\(A, \mu, U \)) defined and studied by Petrovičová in [37].
Definition 4.4
- (i)
\(\psi (x \cdot y) = \psi (x) \cdot \psi (y)\);
- (ii)
if \(x + y \le u_{1}\), then \(\psi (x + y) = \psi (x) + \psi (y)\);
- (iii)
\(\mu_{2}(\psi (x)) = \mu_{1}(x)\);
- (iv)
\(\psi (U_{1}(x)) = U_{2}(\psi (x))\).
In this case, ψ is called an isomorphism, and we write \(U_{1} \cong U_{2}\).
Proposition 4.2
- (i)
\(\psi^{ - 1}(x \cdot y) = \psi^{ - 1}(x) \cdot \psi^{ - 1}(y)\) for every \(x,y \in A_{2}\);
- (ii)
if \(x,y \in A_{2}\) such that \(x + y \le u_{2}\), then \(\psi^{ - 1}(x + y) = \psi^{ - 1}(x) + \psi^{ - 1}(y)\);
- (iii)
\(\mu_{1}(\psi^{ - 1} (x)) = \mu_{2}(x)\) for every \(x \in A_{2}\);
- (iv)
\(\psi^{ - 1}(U_{2}(x)) = U_{1}(\psi^{ - 1} (x))\) for every \(x \in A_{2}\).
Proof
- (i)Let \(x,y \in A_{2}\). Then we have$$\psi^{ - 1}(x \cdot y) = \psi^{ - 1}\bigl(\psi \bigl(x'\bigr) \cdot \psi \bigl(y'\bigr)\bigr) = \psi^{ - 1}\bigl(\psi \bigl(x' \cdot y'\bigr) \bigr) = x' \cdot y' = \psi^{ - 1}(x) \cdot \psi^{ - 1}(y). $$
- (ii)Let \(x,y \in A_{2}\) such that \(x + y \le u_{2}\). Then \(x' + y' \le u_{1}\), and$$\psi^{ - 1}(x + y) = \psi^{ - 1}\bigl(\psi \bigl(x' \bigr) + \psi \bigl(y'\bigr)\bigr) = \psi^{ - 1}\bigl(\psi \bigl(x' + y'\bigr)\bigr) = x' + y' = \psi^{ - 1}(x) + \psi^{ - 1}(y). $$
- (iii)
Let \(x \in A_{2}\). Then \(\mu_{2}(x) = \mu_{2}(\psi (x')) = \mu_{1}(x') = \mu_{1}(\psi^{ - 1} (x))\).
- (iv)Let \(x \in A_{2}\). Then$$\psi^{ - 1}\bigl(U_{2}(x)\bigr) = \psi^{ - 1} \bigl(U_{2}\bigl(\psi \bigl(x'\bigr)\bigr)\bigr) = \psi^{ - 1}\bigl(\psi \bigl(U_{1}\bigl(x'\bigr) \bigr)\bigr) = U_{1}\bigl(x'\bigr) = U_{1} \bigl(\psi^{ - 1}(x)\bigr). $$
Theorem 4.3
Proof
The converse \(H_{\varphi}^{\mu_{2}}(U_{2}) \le H_{\varphi}^{\mu_{1}}(U_{1})\) is obtained in a similar way; according to Proposition 4.2, it suffices to consider the inverse \(\psi^{ - 1}:A_{2} \to A_{1}\). □
By combining the previous results, we obtain the following statement.
Corollary 4.1
- (i)
\(H_{s}^{\mu_{1}}(U_{1}) = H_{s}^{\mu_{2}}(U_{2})\);
- (ii)
\(H_{l}^{\mu_{1}}(U_{1}) = H_{l}^{\mu_{2}}(U_{2})\);
- (iii)
\(H_{k}^{\mu_{1}}(U_{1}) = H_{k}^{\mu_{2}}(U_{2})\).
Remark 4.3
It trivially follows from the above theorem that if \(H_{\varphi}^{\mu_{1}}(U_{1}) \ne H_{\varphi}^{\mu_{2}}(U_{2})\), then the corresponding dynamical systems \((A_{1}, \mu_{1}, U_{1} )\),(\(A_{2}, \mu_{2}, U_{2} \)) are not isomorphic. This means that the proposed φ-entropy distinguishes non-isomorphic product MV-algebra dynamical systems.
5 Conclusions
In the paper we have extended the results concerning the logical entropy of partitions in product MV-algebras provided in [1] to the case of dynamical systems. By using the concept of logical entropy of a partition in a product MV-algebra, we introduced the notion of logical entropy of a product MV-algebra dynamical system and derived the basic properties of this measure of information. In particular, a logical version of the Kolmogorov–Sinai theorem on generators was provided.
In addition, using the concept of the sub-additive generator φ introduced by the authors in [39], we have defined a general type of entropy of a product MV-algebra dynamical system \((A, \mu, U )\), the so-called φ-entropy of a dynamical system \((A, \mu, U )\). The proposed φ-entropy includes the logical entropy and the Kolmogorov–Sinai entropy as special cases: if we put \(\varphi = l\), where \(l: [ 0, 1 ] \to [ 0, \infty )\) is the logical entropy function defined by Eq. (1.2), we obtain the logical entropy of a dynamical system \((A, \mu, U )\), and putting \(\varphi = s\), where \(s: [ 0, 1 ] \to [ 0, \infty )\) is the Shannon entropy function defined by Eq. (1.1), we obtain the Kolmogorov–Sinai entropy of a dynamical system (\(A, \mu, U \)) defined and studied by Petrovičová in [37]. For the proposed φ-entropy \(H_{\varphi}^{\mu} (U)\), we have created an isomorphism theory of the Kolmogorov–Sinai type. It was shown that the φ-entropy \(H_{\varphi}^{\mu} (U)\) distinguishes non-isomorphic product MV-algebra dynamical systems. In this way, we have acquired several instruments to distinguish non-isomorphic product MV-algebra dynamical systems: the logical, the Kolmogorov–Sinai, and the quadratic logical entropy of a dynamical system \((A, \mu, U )\).
As mentioned above (see Example 3.2), the full tribe of fuzzy sets represents a special case of product MV-algebras; the obtained results can therefore be immediately applied to this significant family of fuzzy sets. From the point of view of applications, it is interesting that to a given family \(\mathcal{F}\) of intuitionistic fuzzy sets can be constructed an MV-algebra \(\mathcal{A}\) such that \(\mathcal{F}\) can be embedded to \(\mathcal{A}\). Also, product on \(\mathcal{F}\) can be introduced by such a way that the corresponding MV-algebra is an MV-algebra with product. Hence all results of our paper can be applied also to the case of intuitionistic fuzzy sets.
Declarations
Acknowledgements
The authors would like to thank the editors and the reviewers for their valuable comments and constructive suggestions that have improved the quality and presentation of this paper.
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Funding
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Authors’ contributions
Both authors have contributed significantly and equally in writing this article. Both authors read and approved the final manuscript.
Competing interests
The authors declare that they have no competing of interest.
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