• Medium | LeetCode 221. 最大正方形 | 动态规划


    221. 最大正方形

    在一个由 '0''1' 组成的二维矩阵内,找到只包含 '1' 的最大正方形,并返回其面积。

    示例 1:

    img
    输入:matrix = [["1","0","1","0","0"],["1","0","1","1","1"],["1","1","1","1","1"],["1","0","0","1","0"]]
    输出:4
    

    示例 2:

    img
    输入:matrix = [["0","1"],["1","0"]]
    输出:1
    

    示例 3:

    输入:matrix = [["0"]]
    输出:0
    

    提示:

    • m == matrix.length
    • n == matrix[i].length
    • 1 <= m, n <= 300
    • matrix[i][j]'0''1'

    动态规划

    状态转移方程:

    [d p(i, j)=min (d p(i-1, j), d p(i-1, j-1), d p(i, j-1))+1 ]

    public int maximalSquare(char[][] matrix) {
        int maxSide = 0;
        if (matrix == null || matrix.length == 0 || matrix[0].length == 0) {
            return maxSide;
        }
        int rows = matrix.length, columns = matrix[0].length;
        int[][] dp = new int[rows][columns];
        for (int i = 0; i < rows; i++) {
            for (int j = 0; j < columns; j++) {
                if (matrix[i][j] == '1') {
                    if (i == 0 || j == 0) {
                        dp[i][j] = 1;
                    } else {
                        dp[i][j] = Math.min(
                            Math.min(dp[i - 1][j], dp[i][j - 1]), 
                            dp[i - 1][j - 1]) + 1;
                    }
                    maxSide = Math.max(maxSide, dp[i][j]);
                }
            }
        }
        int maxSquare = maxSide * maxSide;
        return maxSquare;
    }
    
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  • 原文地址:https://www.cnblogs.com/chenrj97/p/14334195.html
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