This paper is about receiving text messages through a noisy and costly line. Because the line is noisy we need redundancy, but because it is costly we can afford very little of it. I start by using well-known machinery for decoding noisy messages (compressed sensing), then I attempt to reduce the redundancy (using random projections), until I get to a point where I use more orthogonal vectors than the space dimension allows. Instead of grinding to a halt or spurting out noise, this method is still able to decode messages correctly or almost correctly. I have no idea why the method works: this is my first reason for writing this paper using a narrative instead of formal scientific style (the second one is that I am tired of writing semi-formal prose, and long for a change).
翻译:本文涉及通过噪音和昂贵的线条接收短信。 因为这条线很吵, 我们需要冗余, 但是因为费用太低, 我们买不起。 我首先使用众所周知的机器解码噪音信息( 压缩感应 ), 然后试图减少冗余( 随机预测 ), 直到我到达一个点, 我使用比空间维度允许的更多正方位矢量。 这个方法不是停止或刺激噪音, 而是仍然能够正确或几乎正确解码信息。 我不知道这个方法为什么有用: 这是我用描述而不是正式科学风格来撰写本文的第一个原因( 第二个原因是我厌倦了半形式礼仪的写作, 并且为了改变时间很长 ) 。