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This paper presents an indirect adaptive control scheme for deterministic plants which are not necessarily minimum phase. Global convergence is established for the scheme in the sense that the closed-loop poles are asymptotically assigned for the given data sequence and the system input and output remain bounded for all time. A key feature of the scheme is that no persistency of excitation condition is required. The algorithm uses recursive least squares with variable forgetting factor, normalized regression vectors, and a matrix gain with constant trace.