  This paper provides an analysis of the linearized inverse problem in
multifrequency electrical impedance tomography. We consider an isotropic
conductivity distribution with a finite number of unknown inclusions with
different frequency dependence, as is often seen in biological tissues. We
discuss reconstruction methods for both fully known and partially known
spectral profiles, and demonstrate in the latter case the successful employment
of difference imaging. We also study the reconstruction with an imperfectly
known boundary, and show that the multifrequency approach can eliminate
modeling errors and recover almost all inclusions. In addition, we develop an
efficient group sparse recovery algorithm for the robust solution of related
linear inverse problems. Several numerical simulations are presented to
illustrate and validate the approach.
