Chapter 3 Review
... max(x), min(x), mean(x), median(x), std(x), sum(x), prod(x), cumsum(x), cumprod(x), sort(x), size(x), length(x) are just a few. Note that x may be a vector (row or column) or a matrix. For matrices, functions typically work on the columns of the matrix to yield their results. (Always best to use hel ...
... max(x), min(x), mean(x), median(x), std(x), sum(x), prod(x), cumsum(x), cumprod(x), sort(x), size(x), length(x) are just a few. Note that x may be a vector (row or column) or a matrix. For matrices, functions typically work on the columns of the matrix to yield their results. (Always best to use hel ...
Chapter 3
... The simplest random number generators are coins, dice and bags of colored balls. Thus in the RRT example above, the interviewee could be given a well-shaken bag of balls. : white balls with probability to answer N question. : Black balls with probability to answer E question. Other machines ar ...
... The simplest random number generators are coins, dice and bags of colored balls. Thus in the RRT example above, the interviewee could be given a well-shaken bag of balls. : white balls with probability to answer N question. : Black balls with probability to answer E question. Other machines ar ...
FMM CMSC 878R/AMSC 698R Lecture 18
... Indeed, in our case the regular basis functions are polynomials up to order p-1, which are obviously can be expressed via other polynomial basis up to order p-1 near arbitrary expansion center. Zero error is provided due to domains of validity are includes hierarchically to larger validity domains. ...
... Indeed, in our case the regular basis functions are polynomials up to order p-1, which are obviously can be expressed via other polynomial basis up to order p-1 near arbitrary expansion center. Zero error is provided due to domains of validity are includes hierarchically to larger validity domains. ...
Random Variables and Measurable Functions.
... Definition 54 The cumulative distribution function (c.d.f.) of a random variable X is defined to be the function F (x) = P [X ≤ x], for x ∈ <. Similarly, if µ is a measure on <, then the cumulative distribution function is defined to be F (x) = µ(−∞, x] . Note in the latter case, the function may ta ...
... Definition 54 The cumulative distribution function (c.d.f.) of a random variable X is defined to be the function F (x) = P [X ≤ x], for x ∈ <. Similarly, if µ is a measure on <, then the cumulative distribution function is defined to be F (x) = µ(−∞, x] . Note in the latter case, the function may ta ...
Error Notes - Department of Civil, Architectural and Environmental
... roundoff error. Within in the range of representable numbers on any computer, there is a finite number of quantities that can be represented. Approximation of number like (1) irrational numbers or (2) rational numbers that do not precisely match one of the values in the set of representable numbers ...
... roundoff error. Within in the range of representable numbers on any computer, there is a finite number of quantities that can be represented. Approximation of number like (1) irrational numbers or (2) rational numbers that do not precisely match one of the values in the set of representable numbers ...
Vectors and Vector Operations
... Proposition 5. Let A be a matrix and let S be the set of all vectors x such that Ax = 0. Then S is a subspace. Proof. Suppose x is in S and t is a number. Since x is in S one has Ax = 0. So A(tx) = t(Ax) = t0 = 0. So tx is in S. Suppose x and y are in S. So Ax = 0 and Ay = 0. So A(x + y) = Ax + Ay = ...
... Proposition 5. Let A be a matrix and let S be the set of all vectors x such that Ax = 0. Then S is a subspace. Proof. Suppose x is in S and t is a number. Since x is in S one has Ax = 0. So A(tx) = t(Ax) = t0 = 0. So tx is in S. Suppose x and y are in S. So Ax = 0 and Ay = 0. So A(x + y) = Ax + Ay = ...
Vectors - Paignton Online
... describe a route between two points using vectors. • There is one absolutely crucial rule here… you can only travel along a route of known vectors! Just because a line looks like it should be a certain vector, doesn’t mean it is! ...
... describe a route between two points using vectors. • There is one absolutely crucial rule here… you can only travel along a route of known vectors! Just because a line looks like it should be a certain vector, doesn’t mean it is! ...
