  An improved inference method for densely connected systems is presented. The
approach is based on passing condensed messages between variables, representing
macroscopic averages of microscopic messages. We extend previous work that
showed promising results in cases where the solution space is contiguous to
cases where fragmentation occurs. We apply the method to the signal detection
problem of Code Division Multiple Access (CDMA) for demonstrating its
potential. A highly efficient practical algorithm is also derived on the basis
of insight gained from the analysis.
