One of well-known results is that the greatest eigenvalue of a nonnegative matrix lies between the smallest and the largest row sum.
一个著名的结果是一个非负矩阵的最大特征值在它的最小行和与最大行和之间。
Of course, you can use a similar approach, by computing the sum of the elements in each row and remembering which row is the smallest you've seen so far.
当然，你可以使用类似的方法，计算每行元素之和并记录下值最小的那一行。
The "cumulative row to binary number" mapping is the same as the previous mapping, but you keep a cumulative sum — a running total — of the row values.
“累积行到二进制数”的映射与上一个映射一样，但是累积行值——每次计算总值。
But if you wanted to create a vector to sum each row, you might be inclined to try the following.
但是，如果希望创建一个向量来求每行的总和，您可能会编写下面这样的代码。
Now let's complicate the problem a bit: you have a two-dimensional array of unsigned integers, and you want to find the row with the smallest sum.
现在我们让问题变得复杂点：你有一个二维的无符号整形数组，你想要找到具有最小和的那一行。
Given a triangle, find the minimum path sum from top to bottom. Each step you may move to adjacent Numbers on the row below.
给出一个三角形，找出从其顶端到底端的最小路径的总和，每次移动是下一行的相邻数字。
Given a triangle, find the minimum path sum from top to bottom. Each step you may move to adjacent Numbers on the row below.
给出一个三角形，找出从其顶端到底端的最小路径的总和，每次移动是下一行的相邻数字。
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