A self-adaptive scaled min-sum algorithm for LDPC decoding based on the difference between the first two minima of the check node messages (Δmin) is proposed. Δmin is utilized for adjusting the scaling factor of the check node messages, and simulation results show that the proposed algorithm improves the error correcting performance compared to existing algorithms.

This paper presents a new data path synthesis algorithm which takes into account simultaneously three important design criteria: testability, design area, and total execution time. We define a goodness measure on the testability of a circuit based on three rules of thumb introduced in prior work on synthesis for testability. We then develop a stepwise refinement synthesis algorithm which carries out the scheduling and allocation tasks in an integrated fashion. Experimental results for benchmark and other circuit examples show that we were able to enhance the testability of circuits significantly with very little overheads on design area and execution time.

Many DSP applications such as FIR filtering and DCT (discrete cosine transformation) require multiplication with constants. Therefore, optimizing the performance of constant multiplication improves the overall performance of these applications. It is well-known that shifting can replace a constant multiplication if the constant is a power of two. In this paper, we extend this idea in such a way that by employing more than two barrel shifters, we can design highly efficient constant multipliers. We have found that by using two or three shifters, we can generate a large set of constants. Using these constants, we can execute a typical set of FIR or DCT applications with few errors. Furthermore, with variable precision support, we can carry out a fairly large class of DSP applications with high computational efficiency. Compared to conventional multipliers, we can achieve power savings of up to 56% with negligible computational errors.