], [8], are closely related to continued fraction com- putations [9], [10], and will produce the characteristic and initial condition polynomials, Q(z) and P(z) of (5.16), whenever the number of available sym- bols K is at least twice the linear span L. Furthermore, this analysis can be performed in real time, in a manner such that more sequence symbols can be inserted into the computation as they become available. If the above procedure is perceived as a threat to the objectives of the SS system design, then the designer must take steps to insure that 2L sequence elements cannot be observed directly from the transmitted signal. Three pos- sible methods for accomplishing this are: (a) Ensure that the linear span of the sequence {bn} (presumably used as a SS carrier of some sort) is much larger than the processing gain of the system, SO that data modulation effects will, with high probability, pre- clude direct observation of 2L sequence elements. (b) Insert erroneous symbols in the transmission of {bn} SO that error-free observation of 2L consecutive sequence elements is virtually impossi- ble. This can be accomplished with very little degradation to system per- formane when high processing gain is employed. (c) Transmit in-band noise along with the SS signal based on {bn}, to insure that no observer will get a "clean look" at the sequence. The cost of this can be made a small fraction of the processing gain. Other methods for insuring transmission security against this threat are left to the ingenuity of the reader. 5.3 MEMORY-EFFICIENT LINEAR GENERATORS 5.3.1 Partial Fraction Decompositions Initial conditions notwithstanding, the basic structural information about a linear generator is contained in its characteristic polynomial, Q(z). Assuming Pseudonoise Generators that the generated sequence {bn} consists of elements from GF(q), the poly- nomial Q(z) will then be over GF(q), i.e., have coefficients in GF(q). However, its roots may not be in GF(q). Let's assume that Q(z) can be fac- tored SO that Q(z) = (5.45)