Fuzzy Lattice Reasoning for Pattern Classification Using a New Positive Valuation Function
FLR training algorithm.
S0. The first input is memorized. an instant, there are Known
Classes memorized in the memory, initially .
S1. Present the next input to the initially “set” family of rules.
S2. If no rules are “set” then
Store input ,
Go to S1.
Compute of the “set” rules.
S3. Competition among the “set” rules:
Winner is rule such that .
S4. The Assimilation Condition:
Both and .
S5. If the Assimilation Condition is satisfied then
Replace by .
“reset” the winner , Go to S2.
We are committed to sharing findings related to COVID-19 as quickly as possible. We will be providing unlimited waivers of publication charges for accepted research articles as well as case reports and case series related to COVID-19. Review articles are excluded from this waiver policy. Sign up here as a reviewer to help fast-track new submissions.