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How to count and guess well: discrete adaptive filters
Robert Elliott
*
,
Hailiang Yang
*
Corresponding author for this work
University of Alberta
Research output
:
Contribution to journal
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Article
›
peer-review
16
Citations (Scopus)
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Mathematics
Discrete State
50%
Discrete Time
50%
Equivalent Measure
50%
Euclidean Space
50%
Idempotent
50%
Markov Chain
100%
Number of Jump
50%
Parameters
50%
Self-Tuning
50%
State Function
50%
State Markov Chain
50%
State Space
50%
Time Markov Chain
50%
Unit Vector
50%
Computer Science
Adaptive Filter
100%
And-States
100%
Hidden Markov Model
50%
Markov Chain
100%
Models
50%
Procedures
50%
Random Perturbation
50%
State Space
50%
Time Markov Chain
50%
Vectors
50%
Earth and Planetary Sciences
Datum
16%
Estimate
33%
Euclidean Geometry
16%
Markov Chain
50%
Model
16%
Observation
50%
Occupation
16%
Parameter
16%
Shape
16%
State
100%
Subject
16%
Time
33%
Value
16%
Vector
16%
Physics
Estimates
66%
Euclidean Geometry
33%
Independent Variables
33%
Markov Chain
100%
Model
66%
Shapes
33%
Value
33%
Neuroscience
Hidden Markov Model
100%