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An adaptive trellis adaptable to read a signal having signal amplitude dropouts includes a standard partial response maximum likelihood (PRML) trellis and an estimating PRML trellisd. The standard trellis is associated with a standard state diagram having standard branches between states. The estima

An adaptive trellis adaptable to read a signal having signal amplitude dropouts includes a standard partial response maximum likelihood (PRML) trellis and an estimating PRML trellisd. The standard trellis is associated with a standard state diagram having standard branches between states. The estimating trellis is associated with an estimating state diagram having estimating branches between states. Each branch has an associated error metric. Each state of the standard state diagram has two estimating branches feeding into that state and each state of the estimating state diagram has two standard branches feeding into that state. The states are connected by paths formed by branches between the states. A path error metric is the sum of all branch error metrics for all of the branches that form the path. The path arriving at one state having the lowest error metric is the expected path to the next state for reading the signal.

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1. An adaptive trellis adaptable to read a signal having signal amplitude dropouts, the adaptive trellis comprising:a standard partial response maximum likelihood (PRML) trellis, the standard PRML trellis associated with a standard state diagram having standard branches between states, wherein a fir

1. An adaptive trellis adaptable to read a signal having signal amplitude dropouts, the adaptive trellis comprising:a standard partial response maximum likelihood (PRML) trellis, the standard PRML trellis associated with a standard state diagram having standard branches between states, wherein a first set of the standard branches produce a non-zero amplitude read signal sample and a second set of the standard branches produce a zero amplitude read signal sample, wherein each state of the standard state diagram has two standard branches feeding into that state, wherein each standard branch has an associated error metric; andan estimating partial response maximum likelihood (PRML) trellis, the estimating PRML trellis associated with an estimating state diagram having estimating branches between states, the estimating branches produce estimated read signal samples that adapt to the amplitude of the signal, wherein each state of the estimating state diagram has two estimating branches feeding into that state, wherein each estimating branch has an associated error metric;wherein each state of the standard state diagram has two estimating branches feeding into that state;wherein each state of the estimating state diagram has two standard branches feeding into that state;wherein the states are connected by paths formed by branches between the states, wherein a path error metric is the sum of all branch error metrics for all of the branches that form the path, wherein the path arriving at one state having the lowest path error metric survives to be identified as the expected path to the next state for reading the signal. 2. The adaptive trellis of claim 1 wherein:the estimating branches produce estimated read signal samples that adapt to the amplitude of the signal in real time. 3. The adaptive trellis of claim 1 wherein:each of the standard PRML trellis and the estimating PRML trellis is an EPR4ML trellis. 4. The adaptive trellis of claim 1 wherein the error metric for a standard branch is:(the amplitude of the read signal sample−target amplitude of the read signal sample){circumflex over ( )}2, where the target amplitude of the read signal sample=1.0, 0.5, 0, −0.5, or −1.0, assuming monopluse peak amplitude is unity. 5. The adaptive trellis of claim 1 wherein the error metric for an estimating branch is:(the amplitude of the read signal sample−target amplitude of the read signal sample*monopulse peak estimated by the path leading to the parallel branch){circumflex over ( )}2, where the target amplitude of the read signal sample=1.0, 0.5, 0, −0.5, or −1.0. 6. A tape drive having a maximum likelihood detector comprising:an adaptive trellis adaptable to read a signal having signal amplitude dropouts, t he adaptive trellis including a standard partial response maximum likelihood (PRML) trellis, the standard PRML trellis associated with a standard state diagram having standard branches between states, wherein a first set of the standard branches produce a non-zero amplitude read signal sample and a second set of the standard branches produce a zero amplitude read signal sample, wherein each state of the standard state diagram has two standard branches feeding into that state, wherein each standard branch has an associated error metric;the adaptive trellis further including an estimating partial response maximum likelihood (PRML) trellis, the estimating PRML trellis associated with an estimating state diagram having estimating branches between states, the estimating branches produce estimated read signal samples that adapt to the amplitude of the signal, wherein each state of the estimating state diagram has two estimating branches feeding into that state, wherein each estimating branch has an associated error metric;wherein each state of the standard state diagram has two estimating branches feeding into that state;wherein each state of the estimating state diagram has two standard branches feed ing into that state;wherein the states are connected by paths formed by branches between the states, wherein a path error metric is the sum of all branch error metrics for all of the preceding branches that form the path, wherein the path arriving at one state having the lowest path error metric survives to be identified as the expected path to the next state for reading the signal. 7. The tape drive of claim 6 wherein:each of the standard PRML trellis and the estimating PRML trellis is an EPR4ML trellis. 8. An adaptive trellis detection method adaptable to read a signal having signal amplitude dropouts, the adaptive trellis detection method comprising:providing a standard partial response maximum likelihood (PRML) trellis;associating the standard PRML trellis with a standard state diagram having standard branches between states, wherein a first set of the standard branches produce a non-zero amplitude read signal sample and a second set of the standard branches produce a zero amplitude read signal sample, wherein each state of the standard state diagram has two standard branches feeding into that state, wherein each standard branch has an associated error metric; and;providing an estimating partial response maximum likelihood (PRML) trellis;associating the estimating PRML trellis with an estimating state diagram having estimating branches between states, wherein the estimating branches produce estimated read signal samples that adapt to the amplitude of the signal, wherein each state of the estimating state diagram has two estimating branches feeding into that state, wherein each estimating branch has an associated error metric;wherein each state of the standard state diagram has two estimating branches feeding into that state;wherein each state of the estimating state diagram has two standard branches feeding into that state;connecting the states by paths formed by branches between the states, wherein a path error metric is the sum of all branch error metrics for all of the branches that form the path; andidentifying a path arriving at one state having a lowest path error metric as the expected path to the next state for reading the signal. 9. The adaptable trellis detection method of claim 8 wherein:the estimating branches produce estimated read signal samples that adapt to the amplitude of the signal in real time. 10. The adaptive trellis detection method of claim 8 wherein:each of the standard PRML trellis and the estimating PRML trellis is an EPR4ML trellis. 11. The adaptive trellis detection method of claim 8 wherein the error metric for a standard branch is:(the amplitude of the read signal sample−target amplitude of the read signal sample){circumflex over ( )}2, where the target amplitude of the read signal sample= 1.0, 0.5, 0,−0.5, or−1.0 , assuming monopulse peak amplitude is unity. 12. The adaptive trellis detection method of claim 8 wherein the error metric for an estimating branch is:(the amplitude of the read signal sample—target amplitude of the read signal sample*monopulse peak estimated by the path leading to the parallel branch){circumflex over ( )}2, where the target amplitude of the read signal sample=1.0, 0.5, 0, −0.5, or −1.0. 13. An adaptive trellis adaptable to read a signal having signal amplitude dropouts, the adaptive trellis comprising:an estimating partial response maximum likelihood (PRML) trellis, the estimating PRML trellis associated with an estimating state diagram having estimating branches between states, the estimating branches produce estimated read signal samples that adapt to the amplitude of the signal, wherein each state of the estimating state diagram has two estimating branches feeding into that state, wherein each estimating branch has an associated error metric, wherein each state of the estimating state diagram has two standard branches feeding into that state;wherein the states are connected by paths formed by branches between the states , wherein a path error metric is the sum of all branch error metrics for all of the preceding branches that form the path, wherein the path arriving at one state having the lowest path error metric survives to be identified as the expected path to the next state for reading the signal.