The most creative tasks in synthesizing pipelined data paths executing software descriptions are determinations of latency and stage of pipeline, operation scheduling and hardware allocation. They are interrelated closely and depend on each other; thus finding its optimal solution has been a hard problem so far. By using simulated annealing methodology, these three tasks can be formulated as a three dimensional placement problem of operations in stage, time step and functional units space. This paper presents an efficient method based on simulated annealing to provide excellent solutions to the problem of not only the determinations of latency and stage of pipeline, operation scheduling and hardware allocation simultaneously, but also the pipelined data path synthesis under the constraints of performance or hardware cost. It is able to find a near optimal latency and stage of pipeline, an operation schedule and a hardware allocation in a reasonable time, while effectively exploring the existing tradeoffs in the design space.

In this paper, we first propose ten new discrimination features of SAR images in the moving and stationary target acquisition and recognition (MSTAR) database. The Ada_MCBoost algorithm is then proposed to classify multiclass SAR targets. In the new algorithm, we introduce a novel large-margin loss function to design a multiclass classifier directly instead of decomposing the multiclass problem into a set of binary ones through the error-correcting output codes (ECOC) method. Finally, experiments show that the new features are helpful for SAR targets discrimination; the new algorithm had better recognition performance than three other contrast methods.

To overcome the target-aspect sensitivity in radar high resolution range profile (HRRP) recognition, a novel method called Improved Kernel Distance Fuzzy C-means Clustering Method (IKDFCM) is proposed in this paper, which introduces kernel function into fuzzy c-means clustering and relaxes the constraint in the membership matrix. The new method finds the underlying geometric structure information hiding in HRRP target and uses it to overcome the HRRP target-aspect sensitivity. The relaxing of constraint in the membership matrix improves anti-noise performance and robustness of the algorithm. Finally, experiments on three kinds of ground HRRP target under different SNRs and four UCI datasets demonstrate the proposed method not only has better recognition accuracy but also more robust than the other three comparison methods.

Crosstalk is a major issue in modern ADSL and VDSL systems. Static spectrum management (SSM), the traditional way to guarantee spectrum compatibility, employs spectral masks which can be overly restrictive and result in poor performance. In this paper, fixed margin iterative water-filling algorithm is investigated in downstream VDSL and ADSL2+ scenario when they are in the same binder. The algorithm can minimize the transmission power and at the same time the overall high-quality service is guaranteed for all the users of the same binder. Simulation results show that ADSL2+ can realize performance gains of up to 80% compared with SSM techniques or ADSL.

A narrowband active noise control (NANC) system is very effective for controlling low-frequency periodic noise. A frequency mismatch (FM) with the reference signal will degrade the performance or even cause the system to diverge. To deal with an FM and obtain an accurate reference signal, NANC systems often employ a frequency estimator. Combining an autoregressive predictive filter with a variable step size (VSS) all-pass-based lattice adaptive notch filter (ANF), a new frequency estimation method is proposed that does not require prior information of the primary signal, and the convergence characteristics are much improved. Simulation results show that the designed frequency estimator has a higher accuracy than the conventional algorithm. Finally, hardware experiments are carried out to verify the noise reduction effect.