Assign numMatches with the number of elements in userValues that equal matchValue.
Ex: If matchvalue = 2 and uservals = [2, 2, 1, 2], then numMatches = 3. function numMatches = Findvalues(uservalues, matchvalue) % userValues: User defined array of values % matchValue: Desired match value arraysize = 4; % Number of elements in uservalues array numMatches = 0: % Number of elements that equal desired match value %
Write a for loop that assigns numMatches with the number of % elements in uservalues that equal matchvalue. end

At an open or uncontrolled intersection, yield if a. your road is paved and the crossroad is not b. the cross road is paved and yours is not c. you have two or more passengers in your vehicle d. you did not yield in the last intersection

Ap practice - performance task response the ap create performance task asks you to write about an abstraction that you developed and wrote into your code. most of the time that means identifying a function or procedure you wrote to "manage complexity" in your program. here is the actual prompt from the create performance task: 2d. capture and paste a program code segment that contains an abstraction you developed individually on your own (marked with a rectangle). this abstraction must integrate mathematical and logical concepts. explain how your abstraction manage the complexity of your program. (must not exceed 200 words) below is a segment of code from an "under the sea" program with a rectangle drawn around a portion of the code identifying an abstraction. imagine that you wrote this and are composing an ap response about how this abstraction manages complexity. (note: ignore the requirement that the abstraction integrate "mathematical and logical concepts" for this practice response. just write about managing complexity). explain how the abstraction marked with the rectangle in the code above manage complexity of this program. write your response here submit

Using least squares fitting, you are to fit the data sets to the following models and solve for the parameters ai , where i is the index of the parameter. the input/output data for the systems are linked in the bblearn site. for each of the systems use matlab to plot the supplied data vs. the model fit on one plot. include your code in the solutions. (a) linear fit "lineardata.mat" y=a1x^3 + a2x^2 + a3x + a4 (b) plant fit "plantdata.mat g(s) = a1/(s + a2)