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In this paper, we propose and study the distributed blind adaptive algorithms for wireless sensor network applications. Specifically, we derive a distributed forms of the blind least mean square (LMS) and recursive least square (RLS) algorithms based on the constant modulus (CM) criterion. We assume that the inter-sensor communication is single-hop with Hamiltonian cycle to save the power and communication resources. The distributed blind adaptive algorithm runs in the network with the collaboration of nodes in time and space to estimate the parameters of an unknown system or a physical phenomenon. Simulation results demonstrate the effectiveness of the proposed algorithms, and show their superior performance over the corresponding non-cooperative adaptive algorithms.