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What is norton's theorem?
Norton's theorem is the current equivalent of Thevenin's theorem.
How do you solve a remainder theorem?
You cannot solve a theorem: you can prove the theorem or you can solve a question based on the remainder theorem.
Why the central limit theorem tells us that it is OK to use the normal distribution to determine probabilities of x?
The Central Limit Theorem (CLT) says no such thing! In fact, it states the exact opposite.The CLT sets out the conditions under which you may use the normal distribution as an approximation to determine the probabilities of a variable X. If those conditions are not met then it is NOT OK to use the normal distribution.
What type of statement must be PROVEN in geometry?
That is a theorem.A theorem.
Can a theorem be proven using a corollary?
No, a corollary follows from a theorem that has been proven. Of course, a theorem can be proven using a corollary to a previous theorem.
What is the significance of the Weierstrass theorem in mathematical analysis?
The Weierstrass theorem is significant in mathematical analysis because it guarantees the existence of continuous functions that approximate any given function on a closed interval. This theorem is fundamental in understanding the behavior of functions and their approximation in calculus and analysis.
Can you apply Norton's theorem in circuits containing diodes and BJTs?
Yes, of course but you must first expand the devices to equivalent circuit models of the appropriate approximation level to get reasonable answers. Such equivalent circuit models will have anywhere from 3 or 4 components to dozens depending on approximation level.
If fuzzy wuzzy wasn't fuzzy why is he fuzzy wuzzy?
because fuzzy wazzy was fuzzy
When you call fuzzy set as fuzzy graph?
fuzzy graph is not a fuzzy set, but it is a fuzzy relation.
Why is fuzzy bear so fuzzy?
fuzzy wuzzy had no hair... therefore he cannot be fuzzy
Why the normal distribution can be used as an approximation to the binomial distribution?
The central limit theorem basically states that for any distribution, the distribution of the sample means approaches a normal distribution as the sample size gets larger and larger. This allows us to use the normal distribution as an approximation to binomial, as long as the number of trials times the probability of success is greater than or equal to 5 and if you use the normal distribution as an approximation, you apply the continuity correction factor.
What is fuzzy system?
 Fuzzy inference is a computer paradigm based on fuzzy set theory, fuzzy if-then- rules and fuzzy reasoning  Applications: data classification, decision analysis, expert systems, times series predictions, robotics & pattern recognition  Different names; fuzzy rule-based system, fuzzy model, fuzzy associative memory, fuzzy logic controller & fuzzy system Fuzzy inference is a computer paradigm based on fuzzy set theory, fuzzy if-then- rules and fuzzy reasoning  Applications: data classification, decision analysis, expert systems, times series predictions, robotics & pattern recognition  Different names; fuzzy rule-based system, fuzzy model, fuzzy associative memory, fuzzy logic controller & fuzzy system
Fuzzy logic previous papers please?
fuzzy logic papers fuzzy logic papers fuzzy logic papers
Fuzzy Wuzzy was a bear Fuzzy Wuzzy had no hair Fuzzy Wuzzy wasn't fuzzy was he?
Fuzzy-Wuzzy (a poem by English author and poet Rudyard in 1892) refers to the Hadenoda warriors who fought the British army in North Africa and the respect of the ordinary British soldier toward them. The name "Fuzzy-Wuzzy" could be entirely English in origin, or it could combine some sort of Arabic pun (by chance based on ghazī, "warrior"). It refers to their butter-matted hair that gave them a unique "fuzzy" look.
Fuzzy wuzzy was a bear?
Fuzzy wuzzy was a bear But Fuzzy wuzzy had no hair So he wasn't fuzzy, wuzzy?
Are fuzzy putunias fuzzy?
Yes they are.
Is salt fuzzy?
Salt is not fuzzy.
