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Parameter
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Ross indexed the following pages under the keyword: "Parameter".

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 Chronaxy Differentiation in developmentEnvironment Evolution Function rules and development of central nervous systemHeredity and function rulesMind (individual) development ofNeuron directing impulsesNirvanophilia Reactions development of reactionsReality nature ofSynapse Rate of crossing Parameter function rules asSpace-time and chronaxy 0179 0180
 Cortex dissociationCortex, motor and epilepsyCortex, removal of functional cortex in hysteriaInstinct, sex in tabesNirvanophilia and masochismPain in tabetics Chronaxy Function rules in central nervous systemImpulse, nervous function rules of nervous impulseInstinct, sex in tabesNeuron function rules of neuronParameter function rules asSynapse Rate of crossingSynapse and epilepsy 0185 0186

 Previous | Next | Cards | Index | Cloud 1940
 Group (mathematical) finite continuousOrganisation parameters ofParameter of organisation 0845 0846
 Inhibition and organisationOrganisation parameters ofParameter of organisationStimulus group structure of Nirvanophilia is wrong 0851 0852
 Excitation and organisationOrganisation parameters ofParameter of organisation 0855 0856

 Previous | Next | Cards | Index | Cloud 1941
 Dominance in organisation Parameter finding 0955 0956
 Dominance test forIndependence test forMathematics completing systemMatrix methodParameter test for 0961 0962
 Summary: A higher level must usually change more slowly than a lower level, in order that the lower level may be given time to catch its neutral point.Dominance and velocityIndependence and velocityParameter if not knownProbability of parameter Summary: If, from a given system, we remove knowledge of a variable, we must introduce probability to replace it. (But see next paragraph) 0971 0972
 Organisation number of parametersParameter number of Summary: We have discussed the situation: p's dominate x's, and x's dominate y's. Under these conditions we can get a stability of organisation. Also we can get y-point in y-space moving twice through the same point in different directions. If the x's react rapidly they will tend to disappear functionally. A succession of such gives transmission through a series of organisations. If one level has only a few, or a single, variable this introduces an essential simplicity into all subsequent levels. A large organisation may be 'simple' because it depends on only one or a few parameters.Equilibrium of organisationsOrganisation exploring organisation 0981 0982
 Break definitionOrganisation breakParameter and break 1001 1002
 Summary: (1) Brain activity will sometimes conduct an animal, with great ingenuity, to its death. (2) Survival is a by-product of brain activity. Summary: It is agreed, with 928, that a reversible system is of no interest from our point of view and does not exist in nature anyway.Neutral point (of equilibrium - including 'cycle', 'region' etc.) effect of change of parameterOrganisation irreversibleParameter and neutral point Summary: We show how to calculate the shift of a neutral point for a small change of parameter when the substitution is given as differential equations, (if finite substitution 927) (if several parameters, 1023)Parameter changes of state of equilibrium 1009 1010
 Summary: Another example of the conclusion of 1006.Brain fundamental functionDeath achievedNeutral point (of equilibrium - including 'cycle', 'region' etc.) effect of change of parameterParameter and neutral pointSurvival by-product Summary: Equations are given for determining the shift in a neutral point if several parameters are altered a little. The change in each coordinate is a linear function of the changes of parameters.Neutral point (of equilibrium - including 'cycle', 'region' etc.) examples 1023 1024

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 Parameter definition 1081 1082
 Parameter for joining two machines Organisation splitting into parts 1107 1108

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 Summary: If r parameters controlling a complete system are arbitrarily under our control, then we can, by controlling the parameters, force an arbitrarily selected set of r variables to behave as we chose. The detailed control can, so to speak, be transmitted through the many other variables without any loss of control!Input control possibleParameter degrees of freedom Summary: Note from Eddington. 1377 1378
 Summary: Orders of velocity make complete systems. Summary: The shift is calculated, of a neutral point as a result of small changes in parameters.Equilibrium shift by parameterParameter changes of state of equilibrium 1475 1476

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 Null-function definedParameter equals null function Summary: Some very simple "variables" do not change, i.e. [x'=0]. These are what used to be called "parameters." 2306 2307

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 Organisation concept abandonedParameter as variable outside system Constraint reaction of homeostat to 2557 2558

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 Summary: A variable of constant intrinsic stability and one that always moves towards some function of its neighbours' states are identical. (Cf. 3110) (Behaviour 3134, 3239)Information in machinesMarkov process / chain affecting a machine Information in a disturbed systemInformation in machinesMarkov process / chain affecting a machineParameter as source of information 3201 3202
 Information in machinesMarkov process / chain affecting a machineMarkov process / chain equilibrium in ensembleParameter as source of informationResting state of system with Markoff parameter Summary: Canonical equations of the densities in state of a system disturbed by an information source. (See 3227) Information in machinesMarkov process / chain affecting a machine 3223 3224
 Markov process / chain information fromParameter as source of informationResting state and information Transition probability and information 3275 3276
 Input control possibleParameter control by 3361 3362

 Previous | Next | Cards | Index | Cloud 1952
 Experience law ofParameter allows information to fallSet or Ensemble parameter and information Summary: Every parameter-change allows (or forces) the information in an ensemble to drop to a new lower level. Same applies to δ-impulse 3936.Habituation theory of 3704 3705
 Control via constantsJacobian (determinant) rank and controlParameter independence among Information loss in function 3778 3779
 Summary: Rank, and control effected by parameters. 3800, 3802, 4301Control via constantsInput control possibleJacobian (determinant) rank and controlParameter control byRank of system with part-function 3798 3799
 Experience Information fall under change of parameterParameter allows information to fall 3954 3955
 DAMS (Dispersive and Multistable System) [71]: The multistable system [SHORTHAND] essential variables are separated, 4226. Summary: The multistable system as merely one of many.Determinate multistable systems as determinateParameter system independent of 4226 4227
 Summary: Effectiveness of parameters with finite substitution. Applied 4414Dimension of parametric controlHistory examplesMemory in systemParameter control exerted by Summary: Examples of states that include history. Summary: Knowledge must be tested by control. 4438Information at runaway Epistemology [17]: Knowledge must mean 'control' if it is to be objective, 4303. 4302 4303
 Parameter dominating systemTransmission from system to systemVariety defined 4312 4313

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 Parameter as essential variables 5574 5575
 These images are reproduced courtesy of The Estate of W. Ross Ashby. Copyright 1972, 2008 © The Estate of W. Ross Ashby

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