I have a small problem in a exercise. So i have to make dynamic vectors with 3 dimentions and calculate the average of the sum of all vector's, how can I do this? example: iftrue V = []; fori=1:5 V1 = [v1 v2 v3]
Actually, I didn't exlain my question very well. Actually I want to take average of elemnet of array. So Z = 6×2 cell array {[1 0 2 2 1 1 3 1 1 0]} {[2 1 0 0 0 1 0 2 0 0]} {[2 2 3 3 1 3 3 2 1 0]} {[2 2 0 0 1 2 0 2 0 0]} ...
Mean:Average or mean value of array(数组的平均值) Median:Median value of array(数组中值) Mode:Most frequent values in array(数组中最常见的值) prctile:Percentiles of a data set(每一个百分数的数值,若求四分位数,则q1为25%,q3为75%) Quartile:四分位数 Quartile:四分位数,通常指q1和q3 Inter...
function[sumArray,averageArray,minArray]=arraystuff(inputArray)sumArray=sum(sum(inputArray));averageArray=mean(mean(inputArray));minArray=min(min(inputArray));end 代码语言:javascript 代码运行次数:0 运行 AI代码解释 [Asum,Aavg,Amin]=cellfun(@arraystuff,A)Asum=45.00003.00007.3668Aavg=5.00000.33330.613...
averageArray = mean(mean(inputArray)); minArray = min(min(inputArray)); end 1. 2. 3. 4. 5. [Asum, Aavg, Amin] = cellfun(@arraystuff,A) Asum = 45.0000 3.0000 7.3668 Aavg = 5.0000 0.3333 0.6139 Amin = 1.0000 0 0.0975 1.
averageproduct = sum(flows_mat .* occupancy_mat, 2) / size(flows_mat, 2); % Display the result disp(averageproduct); This code should work for any number of rows in your data. The code first converts the cell arrays to matrices using the cell2mat function, then calculates the average...
Several executions of this code (including recomputation of y) will produce different approximations to 0.7 and 1. The other reason is that you have a finite length signal. Increasing L from 1000 to 10000 in the example above will produce much better approximations on average. FFT Algorithms ...
average(self.clf_[c], axis=0) # '中心点'是否在误差范围 optimized = True for center in self.centers_: org_centers = prev_centers[center] cur_centers = self.centers_[center] if np.sum((cur_centers - org_centers) / org_centers * 100.0) > self.tolerance_: optimized = False if ...
mean Averageormean value. S = mean(X)isthe mean valueofthe elementsinXifXisa vector.Formatrices, Sisa row vector containing the mean valueofeachcolumn.ForN-D arrays, Sisthe mean valueofthe elements along the first array dimension whose size doesnotequal1. ...
% (where N == 4 here) containing data of input blob(s) and outputs a cell % array containing data from output blob(s) scores = net.forward(input_data); toc; scores = scores{1}; scores = mean(scores, 2); % take average scores over 10 crops ...