The multirate signal processing subband techniques have been recently developed for adaptive filters, since some of the applications such as acoustic echo cancellation and wideband active noise control need adaptive filters with hundreds of taps, which result in high computational complexity and low convergence rate. By the use of Subband adaptive algorithms, the computational complexity may be reduced along with convergence rate; however, a delay is introduced in the signal path. To remove the delay, the delayless subband adaptive filter architecture open loop structures have been introduced. This paper presents a new open loop delayless subband adaptive filter structure with critical sampling, where the performance concerning the mean square error of the subband adaptive algorithm, caused due to the aliasing existing in the subband structure, is superior to the results obtained up to now for open loop delayless structures. In applications like echo cancellation and speech enhancement, where there is need to track continuously, adaptive filtering is usually used. Long adaptive filters gives problems like low convergence and high complexity. Subband adaptive filtering has been introduced to overcome these problems. The filter banks used in subband adaptive filtering introduce large delays. In order to compensate for the delays, delayless subband adaptive filtering is introduced. Delayless subband adaptive filtering is used in both open loop and closed loop configuration, where the subband filters are transformed to a fullband filter using a weight.