Blind equalization of single-input multi-output channels has practical valu
e for inverse problems encountered in communications, sonar, and seismic da
ta processing. Relying on diversity (sufficient number of multiple outputs)
, we bypass the channel estimation step and derive direct blind FIR equaliz
ers of co-prime FIR channels. There are no constraints on the inaccessible
input, apart from a minimum persistence of elicitation condition; the input
can be deterministic or random with unknown color or distribution. At mode
rate SNR (>20 dB), the resulting algorithms remain operational even with ve
ry short data records (<100 samples), which makes them valuable for equaliz
ation of rapidly fading multipath channels. Complexity, persistence of exci
tation order, and mean-square error performance tradeoffs are delineated fo
r equalizers of single-shift (semi-blind). pair, or, multiple shifts estima
ted separately or simultaneously. Optimum and suboptimum combinations of th
e equalizers' outputs are also studied. Simulations illustrate the proposed
algorithms and compare them with dual deterministic channel identification
algorithms.