A Fuzzy Gleason Algebra∗ Presentado en el X Encuentro de Geometr´ıa y sus Aplicaciones en 1999

Abstract For a complete quasi-monoidal lattice L, with some additional properties, we consider the category of Gleason L-algebras.

1

Introduction.

ˇ In their fundamental paper [3], Ulrich H¨ohle and Alexander P. Sostak have constructed the category L − TOP of L-topological spaces together with an interior operator, Manuel Surez in [5] combines the topological operators obtaining a classification in the environment of the set topology and Charles Neville in [4] studies the bitopological spaces in order to obtaining an Gleason algebra, in it is natural to investigate analogous ideas in the categories of Ltopological spaces.

2

Preliminaries.

The basic facts needed in the sequel are presented in this section. We are mainly interested in the basic ideas about cqm-lattices and L-fuzzy topo∗

Coautor: profesor Carlos O. Ochoa Castillo de la Universidad Distrital

Huellas en los Encuentros de Geometr´ıa y Aritm´etica: Joaqun Luna Torres

logical spaces. For the notions and results not discussed here, the reader is referred to reference [2].

2.1

From Lattice Theoretic Fundations.

A complete quasi-monoidal lattice or cqm-lattice is a triple (L, 6, ⊗) which satisfies: I. (L, 6) is a complete lattice where > denotes the universal upper bound and ⊥ denotes the universal lower bound II. (L, 6, ⊗) is a partially ordered groupoid, i. e. ⊗ is a binary operation on L satisfying the isotonocity axiom a 6 b and c 6 d implies a ⊗ c 6 b ⊗ d. III. α 6 α ⊗ >, α 6 > ⊗ α, for all α ∈ L. 2.1.1

The Category CQML

A morphism φ between (L1 , 61 , ⊗1 ) and (L2 , 62 , ⊗2 ) is a map φ : L1 → L2 provided with the properties: m1. φ commutes with arbitrary joins. m2. φ(α ⊗1 β) = φ(α) ⊗2 φ(β). m3. φ preserves universal upper bounds i. e. φ(>) = >. We have the category CQML where the objects are the cqm-lattices and the morphisms are the morphisms between the cqm-lattices. A partially ordered groupoid (L, 6, ⊗) is a cl-groupoid iff ⊗ is distributive over non empty joins, i. e. IV. for J 6= ∅, ! _ _ αj ⊗ β = (αj ⊗ β) j∈J

168

j∈J

and

β⊗

_ j∈J

αj =

_ j∈J

(β ⊗ αj ) .

A Fuzzy Gleason Algebra

2.1.2

Quantales and Cqm-Lattices

A triple (L, 6, ∗), where (L, 6) is a complete lattice, is a quantale if V. (L, ∗) is a semigroup, VI. ∗ is distributive over arbitrary joins, i.e. ! _ _ _ _ αi ∗ β = (αi ∗ β) and β ∗ αi = (β ∗ αi ) . i∈I

i∈I

i∈I

i∈I

A quadruple (L, 6, ⊗, ∗), where (L, 6, ⊗) is a cqm-lattice, (L, 6, ∗) is a quantale and moreover VII. ∗ is dominated by ⊗ i.e. for arbitrary α1 , α2 , β1 , β2 ∈ L we have: (α1 ⊗ β1 ) ∗ (α2 ⊗ β2 ) 6 (α1 ∗ α2 ) ⊗ (β1 ∗ β2 ), is an enriched cqm-lattice. Every quantale is left- and right-residuated i.e. there exist binary operations →r and →l on L satisfying the following axioms: α ∗ β 6 γ ⇔ β ∗ α →r γ

,

β ∗ α 6 γ ⇔ β ∗ α →l γ,

where α, β, γ ∈ L. In particular, →r and →l are determined by: _ _ α →r γ = {λ ∈ L | α ∗ λ 6 γ} and α →l γ = {λ ∈ L | λ ∗ α 6 γ}.

2.2

The Category L − FTOP.

Given (L, 6, ⊗) a cqm-lattice and X a non empty set; an L-fuzzy topology on X is a map T : LX → L satisfying the following axioms: o1. T(1X ) = >, o2. For f, g ∈ LX , T(f ) ⊗ T(g) 6 T(f ⊗ g), 169

Huellas en los Encuentros de Geometr´ıa y Aritm´etica: Joaqun Luna Torres

o3. For every subset {fλ }λ∈Λ of LX the inequality ^ _ T(fλ ) 6 T( fλ ). λ∈Λ

λ∈Λ

holds. If T is an L-fuzzy topology on X, the pair (X, T) is an L-fuzzy topological space. Since the set X is non empty, LX consists at least of two elements. In particular, the universal lower bound in (LX , 6) is given by 1∅ . When we take the empty subset of LX and we apply the axiom o3, we obtain o1’. T(1∅ ) = >. Given T1 and T2 L-fuzzy topologies on X, we say that T1 is weaker than T2 (or T2 is stronger than T1 ) if T1 (f ) ≤ T2 (f ) ∀f ∈ LX , when T1 is weaker than T2 , we denote it with T1  T2 . The relation  is a partial ordering on the set LF − T opX of all L-fuzzy topologies on X; moreover, (L − FTopX , ) is a complete lattice (cf. [3]). Given (X, X) and (Y, Y) L-fuzzy topological spaces; a map φ : X → Y is LF-continuous iff for all g ∈ LY , φ satisfies Y(g) 6 X(g ◦ φ). Thus, we have the category

L − FTOP where the objects are the LF-

topological spaces and the morphisms are the LF-continuous maps.

2.3

The Category L − TOP.

In the following considerations we always assume that (L, 6, ⊗) is an object of CQML. If we need more structure, we will state these additional requeriments explicitly. Given X a non empty set and L an object of CQML; 170

A Fuzzy Gleason Algebra

a subset τ of LX is an L-topology in X iff τ is provided with the following properties: T0. 1X , 1∅ ∈ τ , T1. If f, g ∈ τ , then f ⊗ g ∈ τ , T2. If {fi | i ∈ I} ⊆ τ , then

W

i∈I

fi ∈ τ ,

The pair (X, τ ) is called an L-topological space. Let us consider two Ltopological spaces (X1 , τ1 ) and (X2 , τ2 ); a function ψ : X1 → X2 is Lcontinuous iff for all

g ∈ τ2 we have that g ◦ ψ ∈ τ1 . It is clear that

L-topological spaces and L-continuous functions form a category that we ˇ denote with L − TOP. H¨ohle and Sostak in [3] show that every L-fuzzy topology T in X induces an L-topology τT by τT = {f ∈ LX | T (f ) = >}, and establish the functor F : L − FTOP → L − TOP defined by F(X, T ) = (X, τT ) and F(φ) = φ where φ is a LF-continuous map.

3

Important L-Operators.

Let X be a set, a map I : LX → LX is an L-interior operator (cf. [3]) iff I satisfies the following conditions: I0. I(1X ) = 1X , I1. If f ≤ g, then I(f ) ≤ I(g), I2. (I(f )) ⊗ (I(g)) ≤ I(f ⊗ g), I3. I(f ) ≤ f , 171

Huellas en los Encuentros de Geometr´ıa y Aritm´etica: Joaqun Luna Torres

I4. I(f ) ≤ I(I(f )), it is easy to see that every L-toplogy τ in X induces an L-interior operator Iτ by Iτ (f ) =

_

{g ∈ τ | g ≤ f }

and vice versa, every L-interior operator I produces an L-topology τI defined by τI = {f ∈ LX | f ≤ I(f )}, We add that each LF-topology T in X induces an L-interior operator IT defined by: IT (f ) =

_ {h ∈ LX | h ≤ f and T (h) = >}.

Let X be a set, a map A : LX → LX is an L-adherence map (cf. [5] and [2]) iff A satisfies the following conditions: A0. A(1∅ ) = 1∅ , A1. If f ≤ g, then A(f ) ≤ A(g), V W A2. (A(f )) (A(g)) ≤ A(f g), A3. f ≤ A(f ), A4. A(A(f )) ≤ A(f ), it is easy to see that every LF-toplogy T in X induces an L-adherence map Aτ by AT (f ) =

^

{h ∈ LX | f ≤ h and τ (h → 1∅ ) ∈ L0 }.

This way, given a LF-topology, we have the interior IT and adherence AT operators. We say that (X, S, T) is a comparable LF-bitopological space (cf. [4]) if X is a set and S and T are LF-topologies on X, with the condition S  172

A Fuzzy Gleason Algebra

T. Given (X, S, T) a comparable LF-bitopological space, an element f ∈ S! (L0 ) is called regular if IS AT (f ) = f . Denoting with GST the collection of the regular elements, we are interested in determining the properties of GST . Theorem 3.1. For each comparable LF-bitopological space (X, S, T), the collection GST is a Gleason algebra. Proof. First, let us see that 1X ∈ GST , from A3. we have that AT (1X ) = 1X and for I0. I(1X ) = 1X , i. e. IS AT (1X ) = 1X . To see that 0X inGST , we use A0. and I3.: IS AT (0X ) = IS (0X ) = 0X . Given f, g ∈ GST we want to prove that f ⊗ g ∈ GST ; from f ⊗ g ≤ f and f ⊗ g ≤ g and applying the properties A1. and I1. we obtain that IS AT (f ⊗ g) ≤ IS AT (f ) and IS AT (f ⊗ g) ≤ IS AT (g), therefore, IS AT (f ⊗ g) ≤ IS AT (f ) ⊗ IS AT (g) =f ⊗g

(1)

As each f ∈ GST satisfies that IS (f ) = f and f ⊗ g ≤ AT (f ⊗ g), then f ⊗ g = IS (f ) ⊗ IS (g) ≤ IS AT (f ⊗ g) from (1) and (2) we obtain that f ⊗ g ∈ GST .

(2) 

References [1] Jiri Adamek, Horst Herrlich, George Strecker Abstract and Concrete Categories, John Wiley & Sons (New York, 1990). [2] M. Garc´ıa Marrero et Al, Topolog´ıa, Vol I, Alhambra (Madrid, 1975). 173

Huellas en los Encuentros de Geometr´ıa y Aritm´etica: Joaqun Luna Torres

ˇ [3] Ulrich H¨ohle and Alexander P. Sostak, Fixed-Basis Fuzzy Topologies, In: Mathematics of Fuzzy Sets: Logic, Topology and Measure Theory, Kluwer Academic Publisher (Massachusetts, 1999). [4] Charles W. Neville A Loomis-Sikorski Theorem for Locales, Annals New York Academy of Sciences ( New York 1992). [5] Manuel Suarez M. Topolog´ıa Conjuntista - Una Presentaci´on BuleanaAdjunta, Universidad Pedag´ogica y Tecnol´ogica de Colombia ( Tunja, 1992).

174

A Fuzzy Gleason Algebra.pdf

Whoops! There was a problem loading more pages. Retrying... Whoops! There was a problem previewing this document. Retrying... Download. Connect more ...

122KB Sizes 2 Downloads 145 Views

Recommend Documents

Jackie Gleason and President Nixon view alines at ... - Rense
defense of our own nation. In the 1950s many laboratories at the MIT Lincoln Labs, California. Institute of Technology Labs, Hughes Aircraft Labs, AVCO Everett ...

A Decentralized Adaptive Fuzzy Approach
for a multi-agent formation problem of a group of six agents, .... more realistic solutions for formation control of multi-agent systems. ..... model,” Computer Graphics, vol. ... “Contaminant cloud boundary monitoring using network of uav sensor

FRS 13-14 - Colloquium Poster - Gleason, Macy.pdf
There was a problem loading more pages. Retrying... FRS 13-14 - Colloquium Poster - Gleason, Macy.pdf. FRS 13-14 - Colloquium Poster - Gleason, Macy.pdf.

Supervised fuzzy clustering for the identification of fuzzy ...
A supervised clustering algorithm has been worked out for the identification of this fuzzy model. ..... The original database contains 699 instances however 16 of ...

Fuzzy Grill m-Space and Induced Fuzzy Topology - IJRIT
IJRIT International Journal of Research in Information Technology, Volume 2, Issue 6, June ... Roy and Mukherjee [1] introduced an operator defined by grill on.

Application of Fuzzy Logic Pressure lication of Fuzzy ...
JOURNAL OF COMPUTER SCIENCE AND ENGINEER .... Experimental data has been implemen ... The dynamic process data obtained via modelling or test-.

Fuzzy Grill m-Space and Induced Fuzzy Topology - IJRIT
IJRIT International Journal of Research in Information Technology, Volume 2, Issue 6, June 2014, Pg: .... Definition 3.13:-Let G be a fuzzy grill on fuzzy m-space.

Fuzzy Clustering
2.1 Fuzzy C-Means . ... It means we can discriminate clearly whether an object belongs to .... Sonali A., P.R.Deshmukh, Categorization of Unstructured Web Data.

Fuzzy-KNN5.pdf
There was a problem loading this page. Retrying... Fuzzy-KNN5.pdf. Fuzzy-KNN5.pdf. Open. Extract. Open with. Sign In. Main menu. Displaying Fuzzy-KNN5.pdf ...

Fuzzy Region Competition
provide phone: 86-21-62933739-15; fax: 86-21-62932035; e-mail: ...... BT ε ε ε ε ε ε. L. L. L. (12). According to the e th element e ε adopting 1, in ]0,1[ and 0,.

Adaptive Output-Feedback Fuzzy Tracking Control for a ... - IEEE Xplore
Oct 10, 2011 - Adaptive Output-Feedback Fuzzy Tracking Control for a Class of Nonlinear Systems. Qi Zhou, Peng Shi, Senior Member, IEEE, Jinjun Lu, and ...

Bayesian ART-Based Fuzzy Inference System: A New ...
Here, the antecedent label Ai,k of rule Rk is defined using .... The chosen (i.e., winning) rule Rkp is subsequently defined ... complies with (11) is conducted.

Wall Follower Robot Using Fuzzy Logic: A Review - IJRIT
system that enables a mobile robot in moving through a corridor or following a .... The gain scheduling controller will be used before the FLC to control the error signal ... 2) computing the path winding number, 3) learning a combinatorial map,.

Active noise cancellation with a fuzzy adaptive filtered ...
reduce the weight, volume and cost of the overall noise control system. ... uk drives an anti-noise speaker with transfer function Hs(z), ... Hence, the performance of broadband ..... 2 Bai, M.R., and Lin, H.H.: 'Comparison of active noise control.

Fuzzy Controller Tuning for a Multivariable System ...
When level is near to zero, temperature has an important variation. System parameters are not exactly known and approximate values are used. Level sensor.

Using Fuzzy Cognitive Maps as a Decision Support ... - Springer Link
no cut-and-dried solutions” [2]. In International Relations theory, ..... Fuzzy Cognitive Maps,” Information Sciences, vol. 101, pp. 109-130, 1997. [9] E. H. Shortliffe ...

RFCMAC: A novel reduced localized neuro-fuzzy ...
In the RFCMAC architecture, an arbitrary virtual rule cell is de- noted as Z½j1,... ..... avoid introducing further meta (free) parameter in the system, the value of g is ...

Learning Hierarchical Fuzzy Rule-based Systems for a Mobile ...
mobile robot control must be capable of coping with a high dimensional .... space into a fixed number of linguistic symbols. ... discount rate. The estimated convergence time can .... National Students Conference of National Alliance of.

C205 A Fuzzy Neural Tree Based on Likelihood.pdf
Whoops! There was a problem loading this page. Retrying... Whoops! There was a problem loading this page. Retrying... Page 3 of 59. 17. wlucb rbd3 ihe ...