我认为这是因为在一次下采样操作期间您的信号出现混叠。但是，我在 R 中重新编写了您的代码（包括在下面），但我没有看到我怀疑conv正在做一些奇怪的事情的相同效果。您可能想查看使用shape参数，看看是否有区别。
以下是您的不同变体的四个图：
- 左上：你的。
- 右上角：使用略有不同
x值的变体。
- 左下：你的频率是你的两倍。
- 右下：
x以两倍频率使用略有不同值的变体。
如您所见，在所有四个示例中，红色和黑色完全重叠。
是的，一般来说，这些是不一样的。下面是一个带有锯齿波的例子，两者不对齐。
这是您询问三角波的具体示例。
仅在下面的 R 代码
#43794
#N = 100;
N <- 100
#dsfactor = 3;
dsfactor <- 3
#H = dsfactor*3;
H <- dsfactor * 3
#x = linspace(0,10,N);
x1 <- seq(0,10,10/(N-1))
x2 <- seq(0,10*(N-1)/N,10/N)
#y = sind(18*x);
y1 <- sin(18*x1/180*pi)
y2 <- sin(18*x2/180*pi)
y3 <- sin(36*x1/180*pi)
y4 <- sin(36*x2/180*pi)
#h = ones(H,1);
h <- rep(1,H)
#convyh = conv(y,h);
convy1h <- filter(y1,h)
convy2h <- filter(y2,h)
convy3h <- filter(y3,h)
convy4h <- filter(y4,h)
downsample <- function(signal, factor)
{
return(signal[seq(1,length(signal), factor)])
}
#convyh_ds = downsample(convyh,dsfactor)./H;
convy1h_ds <- downsample(convy1h, dsfactor)/H
convy2h_ds <- downsample(convy2h, dsfactor)/H
convy3h_ds <- downsample(convy3h, dsfactor)/H
convy4h_ds <- downsample(convy4h, dsfactor)/H
#convyh_ds3 = conv(downsample(y,dsfactor),downsample(h,dsfactor))./(ceil(H/dsfactor));
convy1h_ds3 <- filter(downsample(y1,dsfactor), downsample(h,dsfactor))/ceiling(H/dsfactor)
convy2h_ds3 <- filter(downsample(y2,dsfactor), downsample(h,dsfactor))/ceiling(H/dsfactor)
convy3h_ds3 <- filter(downsample(y3,dsfactor), downsample(h,dsfactor))/ceiling(H/dsfactor)
convy4h_ds3 <- filter(downsample(y4,dsfactor), downsample(h,dsfactor))/ceiling(H/dsfactor)
#figure;
#plot(convyh_ds,'DisplayName','downsample(conv)','LineWidth',1);
#hold on;
#plot(convyh_ds3,'DisplayName','conv(downsample)','LineWidth',1);
#grid minor
#legend('show');
#line([0 length(convyh_ds2)],[0 0],'LineStyle','--');
par(mfrow=c(2,2))
plot(convy1h_ds)
lines(convy1h_ds3, col='red')
plot(convy2h_ds)
lines(convy2h_ds3, col='red')
plot(convy3h_ds)
lines(convy3h_ds3, col='red')
plot(convy4h_ds)
lines(convy4h_ds3, col='red')
