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Asymptotic
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What is the difference between best worst and average case complexity of an algorithm?
These are terms given to the various scenarios which can be encountered by an algorithm. The best case scenario for an algorithm is the arrangement of data for which this algorithm performs best. Take a binary search for example. The best case scenario for this search is that the target value is at the very center of the data you're searching. So the best case time complexity for this would be O(1). The worst case scenario, on the other hand, describes the absolute worst set of input for a given algorithm. Let's look at a quicksort, which can perform terribly if you always choose the smallest or largest element of a sublist for the pivot value. This will cause quicksort to degenerate to O(n2). Discounting the best and worst cases, we usually want to look at the average performance of an algorithm. These are the cases for which the algorithm performs "normally."
Which tool is commonly used in the standard improvement model DMAIC Define phase?
The Kano model is most commonly used in the define phase of the DMAIC (define, measure, analyze, improve, and control) standard improvement model.
Which tool is most commonly in the standard improvement model DMAIC define phase?
The Kano model is most commonly used in the define phase of the DMAIC (define, measure, analyze, improve, and control) standard improvement model.
Which tool is most commonly used in the standard improvement model DMAIC (Define Measure Analyze Improve Control) Define phase?
Time Value Analysis
What is the most important step when creating a scenario?
define the correct
Define algorithm and explain its criteria?
algorithm criteria
Describe the various notations used to define the effiency of An algorithm?
notations used to define the efficiency of An algorithm
What is Notation in Algorithm?
hi i am ravi kashyap my email id kashyap.ravi77@gmail.com notations used to define the effiency of An algorithm? what means
How do you find a largest algorithm in c plus plus?
#define max (a, b) ((a) >= (b)) ? (a) : (b)
What are the main steps involved in writing algorithm?
1 Define the problem 2 Analyze the problem 3 Develop an algorithm/method of solution 4 Write a computer program corresponding to the algorithm 5 Test and debug the program 6 Document the program (how it works and how to use it)
Algorithm to determine if a binary tree is strictly binary?
// Author : SAGAR T.U, PESIT #define TRUE 1 #define FALSE 0 int isStrictBinaryTree (struct tree * n) { if( n NULL ) return TRUE; return FALSE; }
How are the expanded algorithm and the standard algorithm different?
They are different because standard algorithm is more common then the expanded algorithm
What is algorithm to write algorithm to the program to access a pointer variable in structure?
Here is the algorithm of the algorithm to write an algorithm to access a pointer in a variable. Algorithmically.name_of_the_structure dot name_of_the _field,eg:mystruct.pointerfield
Which algorithm is more efficient lamport bakery algorithm or black and white bakery algorithm?
Black and White bakery algorithm is more efficient.
How can i write pseudo code for C plus plus if i haven't even wrote the program yet?
You are going about this backwards. First, define the program. Second, describe its algorithm. Third, if needed, write pseudo code. (Sometime, algorithm and pseudo code is the same process.) Fourth, or third, write real code.
What is complsexity of an algorithm?
Complexity of an algorithm is a measure of how long an algorithm would take to complete given
MATLAB code for FIR filter design in rectangular window using genetic algorithm?
Here is an example MATLAB code for designing an FIR filter with a rectangular window using a genetic algorithm: % Define the desired filter specifications Fs = 1000; % Sampling frequency Fc = 100; % Cutoff frequency N = 51; % Filter order % Define the fitness function for the genetic algorithm fitnessFunc = @(x) designFIR(x, Fs, Fc); % Define the genetic algorithm options options = optimoptions('ga', 'Display', 'iter', 'MaxGenerations', 100); % Run the genetic algorithm to find the optimal filter coefficients [x, fval] = ga(fitnessFunc, N, options); % Design the FIR filter using the obtained coefficients filter = fir1(N-1, x); % Plot the frequency response of the designed filter freqz(filter, 1, 1024, Fs); In the above code, designFIR is a user-defined function that evaluates the fitness of an FIR filter design based on its frequency response. The genetic algorithm is then used to optimize the filter coefficients to meet the desired specifications. Finally, the designed filter is plotted using the freqz function.
