Implementation of finite-memory machines within CAST:FSM

1990 ◽  
pp. 86-94
Author(s):  
Alfred Spalt
Keyword(s):  
Finite Memory

LEARNING DYNAMICS AND NONLINEAR MISSPECIFICATION IN AN ARTIFICIAL FINANCIAL MARKET

2009 ◽  
Vol 13 (5) ◽  
pp. 625-655 ◽  
Author(s):  
Christophre Georges ◽  
John C. Wallace
Keyword(s):  
Time Series ◽  
Financial Market ◽  
Consistency Condition ◽  
Nonlinear Structure ◽  
State Variable ◽  
Bounded Memory ◽  
Long Run ◽  
Finite Memory ◽  
Aggregate Dynamics ◽  
True Structure

In this paper, we explore the consequence of learning to forecast in a very simple environment. Agents have bounded memory and incorrectly believe that there is nonlinear structure underlying the aggregate time series dynamics. Under social learning with finite memory, agents may be unable to learn the true structure of the economy and rather may chase spurious trends, destabilizing the actual aggregate dynamics. We explore the degree to which agents' forecasts are drawn toward a minimal state variable learning equilibrium as well as a weaker long-run consistency condition.

DIAGNOSIS USING FINITE MEMORY OBSERVERS ON AN UNKNOWN INPUT SYSTEM

2005 ◽  
Vol 38 (1) ◽  
pp. 13-18
Author(s):  
Guillaume Graton ◽  
Frédéric Kratz ◽  
Jacques Fantini ◽  
Pierre Dupraz
Keyword(s):  
Unknown Input ◽  
Input System ◽  
Finite Memory

Time-domain design of finite-memory digital filters

1968 ◽  
Vol 2 (4) ◽  
pp. 465-483 ◽  
Author(s):  
T.A Brubaker ◽  
D.R Stevens
Keyword(s):  
Time Domain ◽  
Digital Filters ◽  
Finite Memory
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