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


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1930
Chronaxy
Differentiation in development
Environment
Evolution
Function rules and development of central nervous system
Heredity and function rules
Mind (individual) development of
Neuron directing impulses
Nirvanophilia
Reactions development of reactions
Reality nature of
Synapse Rate of crossing
Parameter function rules as
Space-time and chronaxy
0179 0180
Cortex dissociation
Cortex, motor and epilepsy
Cortex, removal of functional cortex in hysteria
Instinct, sex in tabes
Nirvanophilia and masochism
Pain in tabetics
Chronaxy
Function rules in central nervous system
Impulse, nervous function rules of nervous impulse
Instinct, sex in tabes
Neuron function rules of neuron
Parameter function rules as
Synapse Rate of crossing
Synapse and epilepsy
0185 0186

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1940
Group (mathematical) finite continuous
Organisation parameters of
Parameter of organisation
0845 0846
Inhibition and organisation
Organisation parameters of
Parameter of organisation
Stimulus group structure of
Nirvanophilia is wrong
0851 0852
Excitation and organisation
Organisation parameters of
Parameter of organisation
0855 0856

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1941
Dominance in organisation
Parameter finding
0955 0956
Dominance test for
Independence test for
Mathematics completing system
Matrix method
Parameter 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 velocity
Independence and velocity
Parameter if not known
Probability 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 parameters
Parameter 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 organisations
Organisation exploring organisation
0981 0982
Break definition
Organisation break
Parameter 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 parameter
Organisation irreversible
Parameter 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 function
Death achieved
Neutral point (of equilibrium - including 'cycle', 'region' etc.) effect of change of parameter
Parameter and neutral point
Survival 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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1942
Parameter definition
1081 1082
Parameter for joining two machines
Organisation splitting into parts
1107 1108

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1943
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 possible
Parameter 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 parameter
Parameter changes of state of equilibrium
1475 1476

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1947
Null-function defined
Parameter 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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1948
Organisation concept abandoned
Parameter as variable outside system
Constraint reaction of homeostat to
2557 2558

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1951
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 machines
Markov process / chain affecting a machine
Information in a disturbed system
Information in machines
Markov process / chain affecting a machine
Parameter as source of information
3201 3202
Information in machines
Markov process / chain affecting a machine
Markov process / chain equilibrium in ensemble
Parameter as source of information
Resting 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 machines
Markov process / chain affecting a machine
3223 3224
Markov process / chain information from
Parameter as source of information
Resting state and information
Transition probability and information
3275 3276
Input control possible
Parameter control by
3361 3362

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1952
Experience law of
Parameter allows information to fall
Set 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 constants
Jacobian (determinant) rank and control
Parameter independence among
Information loss in function
3778 3779
Summary: Rank, and control effected by parameters. 3800, 3802, 4301
Control via constants
Input control possible
Jacobian (determinant) rank and control
Parameter control by
Rank of system with part-function
3798 3799
Experience
Information fall under change of parameter
Parameter 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 determinate
Parameter system independent of
4226 4227
Summary: Effectiveness of parameters with finite substitution. Applied 4414
Dimension of parametric control
History examples
Memory in system
Parameter control exerted by
Summary: Examples of states that include history.
Summary: Knowledge must be tested by control. 4438
Information at runaway
Epistemology [17]: Knowledge must mean 'control' if it is to be objective, 4303.
4302 4303
Parameter dominating system
Transmission from system to system
Variety defined
4312 4313

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1957
Parameter as essential variables
5574 5575

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