While doing Histogram Stretching, we established that we go pixel by pixel through whole image and apply Histogram Stretching Formula for each pixel. So, for example in the following image, if there are 100 pixels, we would do Histogram Stretching Formula 100 times. Do you think we could do Histogram Stretching for whole

Trace the Perceptron algorithm for the following input. Suppose the actual labels are with respect to a line passing through the origin with normal vector w* = (-1, 1); for example, the true label of (1,0) is '-1' and that of (0,1) is '+1'. The points are ₁ = (0, -1), x2 = (-1,0), x3 = (2,0), x4 = (√√2,1), x5 = (-3,-2). You need to follow the same assumptions as in the example in Slide 6 of Module 10. Show your work and specify the number of mistakes by the algorithm. x5: (-3,-2) 24=(√2,1) 22: (-1,0) xy: (2,0) (0,-1)

Please solve it , theoretical part of digital image processing course ;   - If you have the following image, apply region growing from the shaded seed point using 8-connectivity and a predicate of “the absolute difference is less than or equal 25”.

Using Matlab, plot the following ultrasound pressure wave as a function of x for t =1 P(t, x) = Poe** cos(@t – kx) where a = 0.15 neper/m, where neper is a dimensionless quantity, k = 1 rad/cm, o = 1 rad/s, and Po = 15 N/m2. Submit your ".m" file as well as the resulting graph labeled appropriately.

Write the code in matlab.

Working with Matlab. I need to assign the points P=(4,3,0) and Q=(6,1,2) and the vector n=5i+8j-3k, and find the distance between Q and the plane  containing P with normal vector n. I'm lost tho on what formula I need or how to input it.

Recall that the dot product of two vectors (1d matrices) produces a scalar value. The dot product is slightly confusing as the scalar value produced can have an arbitrary meaning that simply represents the mathematical operations of multiplying and summing. In other words, the dot product can simply represent the linear projection of vector onto the number line. This interpretation will be used repeatedly throughout machine learning as our main goal will be to take some features dotted with some weights/parameters. Once again, this can be though of as projecting our features onto a number line where the projection acts as our prediction! Keep this idea in mind as it might not make complete sense as of yet. It also important to know that the dot product can additionally take on other meanings such as a geometric meaning which represents how similar any two vectors are when projected onto one another. Meaning, how much one vector points in the direction of another. Given the following…

Using MATLAB : Please explain the process of how you constructed your code and provide screenshots of the output, pictures and graph

Plot the curve cos5(x) in MATLAB given x = 0:0.01.2pi. Attach code and plot screenshot.