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A superset of conventional (Boolean) logic that recognizes more than simple true and false values. With fuzzy logic, members of a set have a "degree of membership" that (typically) ranges from 0-100%. For example, the statement, "today is sunny", might be 100% true if there are no clouds, 80% true if there are a few clouds, 50% true if it's hazy and 0% true if it rains all day.
It's not really 'fuzzy' at all, it's just complex logic really. It basically adds human style conventions of 'hot' and 'cold'. In binary logic hot would be 1 and 0 would be cold. In 'fuzzy logic' it's like looking at a bit as a byte instead. Where you could be hot between 0 and 127 and cold between 128 and 255 with or you could split it up into three ranges, hot being one part, 'neutral' being another and cold being yet a third with different ranges inbetween. It's closer to being like state logic than it's name entails.
refer to Sadeh, Father of Fuzzy Logic.
The covnetional logis is 0 or 1. Just 2 states.
The fuzzy logic is 0 to 1. It is infinite states.
we also can add weight for any state as we want.
It is a decision making routine for the other theory.
In this context, FL is a problem-solving control system methodology that lends itself to implementation in systems ranging from simple, small, embedded micro-controllers to large, networked, multi-channel PC or workstation-based data acquisition and control systems. It can be implemented in hardware, software, or a combination of both. FL provides a simple way to arrive at a definite conclusion based upon vague, ambiguous, imprecise, noisy, or missing input information. FL's approach to control problems mimics how a person would make decisions, only much faster
ordinary logic is just the digital logic (0 and 1)
fuzzy logic is mainly related with Artificial Intelligence here we give inputs and train the circuit to give certain outputs so that it can give outputs similar to the way we think
i suggest you to take a glance at the begining of many fuzzy logic ebooks uploaded there like" Fuzzy Logic for Embedded Systems Applications"
do search at eda ebook you will find more
I don't know if this is going to clarify things at all but if you think of logic as a scale; Standard simple binary logic if there is even 1 bit of difference between one side of the scale and the other the answer changes from 100% to 0% based on that single bit alone. Fuzzy logic would be better called weighted logic, where things are calculated and added and then weighted against each other. So the scale can have a range of values. The only real difference is the level of complexity, and that means that 'fuzzy logic' is just a buzz word it doesn't really mean anything just something people came up with to sound new and innovating. You could call any simple program that takes in raw binary data and outputs a proccessed value based on that as 'fuzzy logic' To people more serious about it the way the logic is weighted has a lot more of a structure to it. That's all that those books are going to tell you is how they weight it and the standards they've come up with. Don't know if there are any IEEE or similar standards that exist for fuzzy logic.
Not really NTFS.. Fuzzy logic routines can be broken down to standard logic routines but more resemble processor functions than logic routines. At it's core it's still binary logic, it just uses a whole byte (or more) as it's standard unit of measure instead of a bit. It's almost like the difference between Assembly language and any higher level language. In ASM you deal generally more with individual bits and addresses. In higher order programming languages you deal with tokens or symbols that perform functions which you don't generally have direct control over. The real difference between 'fuzzy' logic and 'normal' logic is the level of abstraction from the core building blocks.
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