Stride length is the distance between each step, and rhythm is how often you take each step.

长是指每一间的距离，节奏是你每一的频率。

What does it mean to improve your stride length?

提高长意味着什么？

Stride length is a measure of how effective the action you take is with respect to your goal.

长是衡量你所采取的行动对你的目标有多大成效的一种方法。

Use deliberate practice to enhance your skills, and subsequently, your stride length.

通过刻意练习来提高你的技能，进而提高你的长。

So how do you improve your stride length?

那么要如何提高长？

Now, after stride length, the final component is rhythm: how often you take a stride.

在，在长后，最后一个组成部分是节奏：你迈出幅的频率。

Your stride is made up of two components: stride length (L) and rhythm (Y) .

长（L）和节奏（Y）。

Which obviously can only happen if we're taking infinitely small steps every time.

显然，这只有在每次我们都采取无限小的长时才可能发生。

This alternate solution gives a richer understanding that can let you answer other questions about the setup, and it's also core to how I coded accurate simulations of these blocks without requiring absurdly small time steps and huge computation time.

这个替代解决方案提供了更丰富的理解， 可以让你回答关于该设置的其他问题，同时也是我编码这些块的精确模拟的核心方法， 无需使用荒谬的小时间长和巨大的计算时间。

I love that there's like a fractal dynamics of the brain that if you zoom out, you draw the box and you increase that box by certain step sizes, you're gonna see the same statistics.

我喜欢大脑具有类似分形动力的特点， 也就是说，当你放大观察时， 画出一个框并按一定长扩大这个框，你会看到相同的统计规律。

Intagliata: Multiply step length by step rhythm, and you get a speed of 1.28 meters per second, or about 2.9 miles per hour.

伊塔利亚塔：将长乘以频，你得到的速度是每秒1.28米， 或大约每小时2.9英里。

Meanwhile, an improved self-adaptive bat algorithm with step-controlled and mutation mechanisms is proposed herein.

同时，本文提出了一种改进的自适应蝙蝠算法，该算法结合了长控制与变异机制。

And instead of describing the step size as delta theta, a  concrete finite amount, we instead describe it as " d" theta, which I like to think of as signaling  the fact that some kind of limit is being taken.

而不是将长描述为德尔塔 theta，一个具体的有限数量， 我们将其描述为“d” theta，我喜欢将其视为某种极限正在被取的一个信号。

But what the normal distribution is it's the continuous probability density function so it can tell us what's the probability of being 2.183 feet away?

但正态分布实际上是一个连续的概率密度函数，因此它能告诉我们距离为2.183英尺的概率是多少？显然，这种情况仅在我们每次都采取无限小的长时才会发生。

And we scaled it up to the size of our T. rex. And that gives you step length.

我们将它放大到霸王龙的尺寸。这就给出了长。