hi, i completed my M.tech in DSP. I did my project on " Implementation of Mixed MultiBand PrototypeWaveform InterpolationZinc Function Excitation (MMBEPWIZFE) Speech coder. here i used Zinc pulses i used for reconstructing the speech signal at the decoder instead of normal Dirac delta pulses". Here I got one doubt, " why can't we use pureSinc or Cosc signal". and I am giving the full details of ZINC function.please clarrify it . Zinc Basis Functions [Sukkar89] suggest that a signal representation based on "orthogonal function decomposition" can be done via a set of basis functions that have similar characteristics to the signal being modeled. The "zinc basis functions" are proposed to model LPC excitation signals (that are inherently bandlimited and pulsetype). The zinc function is defined as: Z(t) = A Sinc(t) + B Cosc(t), where Sinc(t) = [sin(2*pi*fc*t)]/(2*pi*fc*t) and and Cosc(t)= [1  cos(2*pi*fc*t)]/(2*pi*fc*t) here A,B and fc (cutoff frequency) are constants. Time shifted zinc functions: Z(tk) = A Sinc(tk) + B Cosc(tk). Each Zinc function is itself composed of orthogonal functions Sinc(tk) and Cosc(tk), for any value of k. It can be proved the orthogonal set of (weighted) zinc functions can fully span the space of all bandlimited signals. r(t) = sum{Z(t)} = sum { A Sinc(tnT) + B Cosc(tnT) }, where k=nT. An upsampled residual y(n) is computed. The goal is to optimally represent y(n) with a finite order zinc function model yz(n). A mean sq error L between y(n) and yz(n) is minimized to compute the parameters A and B giving an optimal porder model corresponding to the P smallest values of L. It has been shown that for the same order, the zinc function model is superior to the Fourier series model (for voiced signals). Unvoiced signals are represented using white noise source. Zinc funtions are shown to closely model the perceptually important pitch pulses with a relatively loworder model. Several techniques are proposed to minimize the "roughness" heard in the synthetic speech, due to secondary pitch pulses in the excitation. thanks in advance. ravichandra Win TVs, Bikes, DVD players and more!Click onYahoo! India Promos 

regading PWIZFE speech coder
Started by ●August 29, 2003
Reply by ●September 2, 200320030902
Hi ravi, One simple explanation of using both sinc and cosc functions to model a signal is that these two functions are respectively evn and odd function. Thus, sinc function is more suitable to model the even part of the signal and cosc the odd part. Using only one of them leads to the use of a much higher order to reach the same approximation in case when you use both functions. BTW, is it possible to have a copy of your project report ? Best regards 