Signal fundamentals

I just finished reading the fundamentals chapter about signals (linearity,causality,memory and time invariance). I wanted to solve some exercises and I found this one.

We have a signal with output described by $$y(t) = \int_t^{t+1}x(\tau-a)\;d\tau ,a\in R$$

1. find if the system has memory, is stable, time invariant and linear
2. which values of $a$ make the system causal

I am trying to understand things here. The system has memory if $a<0$ and memoryless $a>0$? I don't know from where to start to find the others.

EDIT

To prove linearity I did this

$$y(t)=F\{x(t)\}$$ $$F\{c_1x_1(t)+c_2x_2(t)\}$$ $$\int_t^{t+1}c_1x_1(\tau -a)+c_2x_2(\tau -a)d\tau$$ $$=\int_t^{t+1}c_1x_1(\tau -a)d\tau +\int_t^{t+1}c_2x_2(\tau -a)d\tau$$ $$=c_1y_1(t) + c_2y_2(t)$$

time invariance

$$F\{x(t-t_0)\}$$ $$=\int_t^{t+1}x(\tau -a-t_0)d\tau$$ $$=\int_{t-t_0}^{t+1-t_0}x(u -a)du$$ so $$=\int_{t-t_0}^{t+1-t_0}x(\tau -a)d\tau$$

which means it is time invariant

Am I right?

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Have you been already told about Fourier transforms and frequency response of the system? – Ilya Mar 22 '12 at 11:00
I know about frequency response but not Fourier. I am not there yet. – john_paker Mar 22 '12 at 11:03
Maybe you should ask the moderators to move this question to the signal processing site dsp.SE. – Dilip Sarwate Mar 22 '12 at 11:24
@DilipSarwate It is not about dsp. – john_paker Mar 22 '12 at 11:28
Did I say that your question was about dsp (digital signal processing)? I recommended moving the question to the signal processing site dsp.SE where discussions deal with signal processing in general, not just dsp. – Dilip Sarwate Mar 22 '12 at 11:36

First, note that the output signal at time $t$ is formed by integrating the values of the input over a unit length interval: $[t-a,t+1-a]$ (a continuous average).

Then, it should be evident that the system is linear (integration is, like the sum, a linear operator), and time-invariant (the relation of input-output does not change over time). And it's certainly not memoryless (the output at time $t$ does depend on other values besides the input at time $t$). To be causal, the output at time $t$ should depend only on "past" values of the input. For example, if $a=0$ or $a=0.5$, it 's NOT casual.

All this is rather informal, if you need to proof these facts formally, this is a start, bu t you should work this out in detail.

If you have learned about the input response $h(t)$, you can also find out that the system is indeed described by a $h(t)$, which is non-zero (actually, 1) over the interval $[a-1,a]$. Once you see this, (and you are supposed to see this quickly when you have some training in signals) you can answer immediately all the original questions.

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I edited my question. I think I proved linearity. I am struggling to prove the others. – john_paker Mar 22 '12 at 12:06
About causality. Does this means that it is causal only for a = 1? – john_paker Mar 22 '12 at 12:43
@john_paker: rather, it's casual for $a \ge 1$ – leonbloy Mar 22 '12 at 13:41
Thanks for your help. I now understand what is going on. – john_paker Mar 22 '12 at 18:58