In this paper, we study unequal error protection (UEP) capabilities of punctured convolutional codes. For constructing the good UEP convolutional codes, the conditional weight distributions of UEP convolutional codes are defined and evaluated. The conditional weight distributions are computed by using the transfer functions of time-varying trellis structures of punctured convolutional codes. The best UEP convolutional codes from the viewpoint of the weight distributions are listed.

For the digital watermarking patchwork algorithm originally given by Bender et al., this paper proposes two improvements applicable to audio watermarking. First, the watermark embedding strength is psychoacoustically adapted, using the Bark frequency scale. Second, whereas previous approaches leave the samples that do not correspond to the data untouched, in this paper, these are modified to reduce the probability of misdetection, a method called full index embedding. In simulations, the proposed combination of these two proposed methods has higher resistance to a variety of attacks than prior algorithms.

A novel self-synchronizable decoding algorithm for transmissions with redundant information is proposed. We assume that desynchronization occurs because a continuous deletion of bits in the channel. The decoder bases its decision on a metric which involves the syndrome and the Hamming distance between certain codeword and its corresponding updated codeword after one iteration of sum-product decoding. The foundation of the previous assumption relies on what we called "CP-distance." The larger the CP-distance of a code the better the synchronization characteristics. Moreover, our proposal is not restricted to cyclically permutable (CP) codes as previous proposals. Theoretical foundation and experimental results show good performance of our algorithm.

In this paper, a rate k/n punctured convolutional code is considered as a time-varying code with period k. The punctured convolutional codes with time-varying constraint length are studied. For these codes, new maximum likelihood decoding techniques are proposed. Not only for the binary symmetric channel but also for any discrete memoryless channel, these decoding techniques can periodically reduce the number of survivors and comparisons in the decoding process. On the basis of the proposed decoding techniques, new classes of punctured convolutional codes are introduced. Computer searches are perfermed to construct good codes from these classes.