denosing given signal using wavelet let us suppose that we have given following model

$y(t)=A_1 \sin(\omega_1*t+\phi_1) + A_2 \sin(\omega_2*t+\phi_2) + A_3 \sin(\omega_3*t+\phi_3)+ \ldots +A_p \sin(\omega_p*t+\phi_p)+z(t)$

where  $z(t)$ is white noise,we have everything unknown,$p,A_i,\omega_i,\phi_i$,what i want to remove noise using wavelet,i know that is it  possible using discrete wavelet,so which mother waveelt is good for deterministic and  periodic components?let us suppose that we have  data  ,some numbers of length $N=294$,which mother wavelet should i choose and  which scales?please help me with practical example,because wavelet is new and i want to see what is steps for denoising,there is some link about denosing

http://eeweb.poly.edu/iselesni/DoubleSoftware/signal.html

including matlab codes,but i want to know before i start use some method  ,is it relevant for such model?as i know wavelet is good for transient signals,is it ok for steady signals?for periodic ones?if so then which steps is necessary?thanks in advance
If you have reason to believe your signal is sparse in the frequency domain, they you should be denoising in that: use FFTs, not wavelets. Look at the magnitude spectrum and see if it's very spiky, and that will be your cue. If so, attenuate the frequencies with a small response.