Presentation is loading. Please wait.

Presentation is loading. Please wait.

Physics of Information (Mathematical Modeling) Infinity Kills Information or the Battle of the „Fly“ for the Datas don‘t tell me, you cannot define something.

Similar presentations


Presentation on theme: "Physics of Information (Mathematical Modeling) Infinity Kills Information or the Battle of the „Fly“ for the Datas don‘t tell me, you cannot define something."— Presentation transcript:

1 Physics of Information (Mathematical Modeling) Infinity Kills Information or the Battle of the „Fly“ for the Datas don‘t tell me, you cannot define something but do it

2 Actual Mathematics n Set Øtotality of elements of which none occur more than once n Representation of Sets Øby listing individual elements {a, b, c, d} Øby describing a common, set specific property, which all elements of the set have and all elements which do not belong to the set don’t have F particular attribute value : { x | x is green) F regulation for generating : { y | 3*n = y, with n = natural number } n Underhand Conditions Øa) each element of a set has at least 2 different values F value #1 - set specific property with constant value for all elements F value #2 - identity with a unique value for each element of the set Øb) value #1 is constant in time F consider all the „For All“ conditions of definitions and theorems: what would happen if elements of a set could disappear? êSee HandOut #1

3 Information Mathematics n Clearance of Underhand Condition a) ØElement of a set is defined by at least 2 changeless values; F #1 equal for all elements of the given set (type) F #2 unique for each element in the given set (individuality) Øany other property of elements of the given set will be ignored n Clearance of Underhand Condition b) ØValue is defined as state of a property by using a relation between 2 elements of sets F the 1. element is called quality and constant in the relation F the 2. element is called value and variable in the relation n Annex F a change of values a -> w of a quality e is called „Transformation“ X ( e | a ) = e | w F a repeatable Transformation will create the same result for the same initial state

4 Axiom of Information Mathematics n Structural Axioms ØLinking of dynamic elements X („connection in series“) ØExistence of a Zero-Element (neutral element) X 1 F = no-change, constancy ØExistence of an Inverse X -1 of X F = reversing the transformation X n ==> {X 1, X, X -1 | X is dynamical element of the element of quality e} Ø is „Group“, if transformation X is „repeatable“ Ø==> focus on repeatable X n {X 1, X rep, X -1 } =: Information about quality e Øvalue area of e: set of all values which can be allocated to e by its dynamic elements

5 Information is n {X 1, X rep, X -1 } Øforeseeable, calculable n ==> Distinctness Øfrom the set Øm = mass, a = acceleration, E = energy, c = speed of light n ==> Repeatability Øfrom the group ØF = m * a ØE = m * c 2 n ==> Change Øfrom the dynamic elements Øproblem of actual mathematics and so actual physics: only describable by „element hopping“ of functions

6 Outside Information is n Chaos Ønothing to be managed, controled or foreseen F but even so exerting influences by creating changes F like falling stars n Excluding Rules of Information Processing: Øoutside information there exist F no rules F no limits F no reliability n Conclusion Øno absolute solution possible - one for all doesn‘t exist F because outside exists unforeseeable (cp. Gödel,incompleteness) Ø1. step: detection of information - EE- Partitioning Ø2. step: protection of information

7 EE Partitioning n Information Øinformation shapes environment through repeatability Øinformation forces adaptation, promotes processing Øprocessing is change F only if repeatable & distinct: information n Messages: cumulative value change Øtraces of dynamic elements Øonly track of information n Information processing = information + processing Øsender acts Ørecipient acts

8 EE Partitioning n parts of message from sender n parts of message from recipient Øorigin Øresult Øcause Øeffect Øaction Øreaction Øunknow process ==> object of interest Øwellknown process ==> no need for knowledge besides n parts of message Øfrom sender Øfrom recipient

9 EE Partitioning n EE Partitioning Øendogenous view = viewing an object of interest independent of its surrounding environment, at its stable identification F every fact of interest is a message about „something“ ==> view „something“ individually Øexogenous view = viewing an object of interest in interaction and relation with its surrounding environment, at its dynamical interactions F every accepted message is processing ==> view „something“ in it‘s effect on the environment, therefore on the recipient as well

10 Protection of Information in SW n Repeatability = Separating data and functions Øprovide repeatability by control of the states of your objects F objects depending on system state can be used like variables F objects depending on their own values, especially input parameters, you can use like variables n Distinctness = Separating objects into data structures Øno tricks, no masquerades of datas to be stored F safety of datas in distributed environments, despite alteration of SW n Change = Separating phases Øprotocol phases, especially in/output F precondition for prognosis

11 Topology of Information Processing n Precondition ØInformation is repeatable & distinct action Øaction follow the principle of least action ØInfinity Kills Information - outside information is chaos n Rules Ødetect information by memory F distinctness: map properties and valuesshape the objects F repeatability: count occurencescrystallize the rules F change: declare interfacescontrol the borderlines Øprotect information by unbreakable rules F define clear chains of action, avoid cycles and ambiguities therein F provide control by minimizing chains of action Øtame infinity by aims F aims and goals as rating scales to single out the needful things êevaluate input, create finite sets of input datas êreach decisions, learn to ignore

12 Topology of Information Processing n Conclusion - the „Fly“ ¡decision ðoutput ðinput Øshort ways Øvectored courses Ødistributed load

13 Measurements of Datastructures (4fF-Method) n Datastructure = Frozen Information ØDatastructure contain states of described objects ØView Fields as presentation of elements of qualities F count values: Eigen weighting g e = 1 / k-1 k > 1, k = number of valuesk > 1, k = number of values F count occurences: Profil weighting g p = T / p T = number of occurencies, p = number of filesT = number of occurencies, p = number of files F count distance: Portal weighting g pd = P / p P = portal distance from input, distance = minimum threadP = portal distance from input, distance = minimum thread F count distance: Exit weighting g ed = E / p E = exit distance to outputE = exit distance to output ØType Fields in endogenous view F field-related typeT f = ( g e, g p ) ØType Fields in exogenous view F task-related type T a = ( g pd, g ed )

14 Field-related field type n Accentuating ØT f = ( +, - ) F few values, small field of application Ønormed value sets, scales Øexample: F for people: sex, title n Descriptive ØT f = ( -, - ) F many values, small field of application Øoften text fields Øexample: F free entry fields n Classifying ØT f = ( +, + ) F few values, large field of application Øorganizational elements for sorting, classifying Øexample: F companies, booking circles, business areas n Documenting ØT f = ( -, + ) F many values, large field of application Øoften identifiers Øexample: F customers, orders, voucher numbers gege gpgp

15 Task-related field type n Evaluating ØT a = ( +, - ) F high portal weighting F low exit weighting Øevaluations Øexample: F pie charts from statistics n Recording ØT a = ( -, - ) F low portal weighting F low exit weighting Ørecords, protocols Øexample: F order values n Diverting ØT a = ( +, + ) F high portal weighting F high exit weighting Øsystem files Øexample: F file of registered user with data station data n Stamping ØT a = ( -, + ) F low portal weighting F high exit weighting Østamp data Øexample: F changing users, alteration date g pd g ed Part II


Download ppt "Physics of Information (Mathematical Modeling) Infinity Kills Information or the Battle of the „Fly“ for the Datas don‘t tell me, you cannot define something."

Similar presentations


Ads by Google