A new algorithm for speech enhancement based on the iterative Wiener filtering method due to Lim-Oppenheim [1] is presented. We propose the use of a generalized non-quadratic cost function in addition to the classical MSE term (quadratic term). The proposed cost function includes two signal-error cross- correlation terms and a L2 norm term of the filter weights. The signal-error cross- correlation terms reduce both the residual noise and the signal distortion in the enhanced speech. The L2 norm term of the filter weights reduces the overall gain of the filter, decreasing the weight noise variance and removing the side lobe of the filter response. Two solutions to the new cost function are presented: the classical non-causal type (ideal Wiener), working in the frequency domain; and a causal finite length in the time domain. In both cases, as Lim's algorithm, the filter output of each iteration is used as "noiseless" speech signal for the following one. Simulation results demonstrate the effectiveness of these algorithms.