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< p > Given an integer array < code > nums< / code > , return < em > the length of the longest < strong > strictly increasing < / strong > < / em > < span data-keyword = "subsequence-array" > < em > < strong > subsequence< / strong > < / em > < / span > .< / p >
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< p > < / p >
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< p > < strong class = "example" > Example 1:< / strong > < / p >
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< pre >
< strong > Input:< / strong > nums = [10,9,2,5,3,7,101,18]
< strong > Output:< / strong > 4
< strong > Explanation:< / strong > The longest increasing subsequence is [2,3,7,101], therefore the length is 4.
< / pre >
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< p > < strong class = "example" > Example 2:< / strong > < / p >
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< pre >
< strong > Input:< / strong > nums = [0,1,0,3,2,3]
< strong > Output:< / strong > 4
< / pre >
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< p > < strong class = "example" > Example 3:< / strong > < / p >
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< pre >
< strong > Input:< / strong > nums = [7,7,7,7,7,7,7]
< strong > Output:< / strong > 1
< / pre >
< p > < / p >
< p > < strong > Constraints:< / strong > < / p >
< ul >
< li > < code > 1 < = nums.length < = 2500< / code > < / li >
< li > < code > -10< sup > 4< / sup > < = nums[i] < = 10< sup > 4< / sup > < / code > < / li >
< / ul >
< p > < / p >
< p > < b > Follow up:< / b > Can you come up with an algorithm that runs in < code > O(n log(n))< / code > time complexity?< / p >