trie time complexity

The K-largest number in the array can be obtained based on the fast sorting method. The steps are as follows: 1. Randomly select a fulcrum 2. Place the number greater than the pivot point to the left of the array. Place the number smaller than the pivot point to the right of the array. Place the pivot point to the center (left) 3. Set the length of the left part to L, When K When K> L, find the number (K-L) in the part recursively When K = L, returns the Split points (that is, the fulcrum of the

The number of K-large in the array can be based on the idea of fast ordering, as follows: 1. Select a fulcrum at random2, will be larger than the fulcrum of the number, put to the left of the array, the number of smaller than the fulcrum to the right side of the array, put the fulcrum in the middle (belong to the left part)3, set the length of the left part is L,When K When K > L, recursively find the number of the first (K-L) in the section When k = L, return the left and right parts of the sp

Question: There is an unordered positive integer group with a 2n number of elements. Required: How can I divide this array into two arrays with N numbers and make the two subarrays closer to the nearest one? 1 1 2-> 1 1 vs 2 Generally, the time complexity of the solution is greater than or equal to O (N ^ 2 ). A sudden burst of inspiration, and a new solution, should be considered a dynamic planning process

The definition of a return string: "Return string" is a string with the same reading and reverse reading. For example, "level" or "Noon" is a return string. A substring, as the name implies, that is, a substring in a string that meets the background nature. Some questions are often discussed around the reply substrings. For example, poj1_4 is the longest reply string and the length of the longest reply string is obtained. The simple algorithm scales each character in turn to both sides. Obvious

the time complexity of recursive algorithms is not linear unless there are only the first two items, and memory consumption. We use the most common Fibonacci series to describe: FunctionFibonacci (n ){If(N = 0 | n = 1){ReturnN ;}Else{ReturnFiber-ACCI (n-1) + fiber-ACCI (n-2);}} This is the most common writing method, which is extremely memory-consuming. When the parameter n is greater than 30, it will

number. The expected complexity of the queue is O (Nlogn), because the fast row will be recursively processed on both sides of the partition, while the K large number only needs to deal with the dividing side, and its expected complexity will be O (n). See "Introduction to Algorithms" for detailed proof.We can think of this roughly:Assuming our data is random enough, each division is in the middle of the d

PrefaceGenerally, for a given algorithm, we need to do :If F (n) is set to algorithm A in the worst case of F (N), if F (n) belongs to algorithm (G (n )), then, the maximum time complexity of algorithm A is g (n), and g (n) is F (n.If F (n) is set to algorithm A in the worst case of F (N), if F (n) belongs to Ω (G (n )), then, the lower limit of the approximate time