A sparsely encoded Willshaw-like attractor neural network based on the binary Hebbian synapses is investigated analytically and by Computer simulations. A special inhibition mechanism which supports a constant number of active neurons at each time step is used. The informationg capacity and the size of attraction basins are evaluated for the Single-Step and the Gibson-Robinson approximations, as well as for experimental results.