Compressed sensing (CS)-based wideband spectrum sensing approaches have attracted much attention because they release the burden of high signal acquisition costs. However, in CS-based sensing approaches, highly non-linear reconstruction methods are used for spectrum recovery, which require high computational complexity. This letter proposes a two-step compressive wideband sensing algorithm. This algorithm introduces a coarse sensing step to further compress the sub-Nyquist measurements before spectrum recovery in the following compressive fine sensing step, as a result of the significant reduction in computational complexity. Its enabled sufficient condition and computational complexity are analyzed. Even when the sufficient condition is just satisfied, the average reduced ratio of computational complexity can reach 50% compared with directly performing compressive sensing with the excellent algorithm that is used in our fine sensing step.

The sparse Fourier transform (SFT) seeks to recover k non-negligible Fourier coefficients from a k-sparse signal of length N (k«N). A single frequency signal can be recovered via the Chinese remainder theorem (CRT) with sub-sampled discrete Fourier transforms (DFTs). However, when there are multiple non-negligible coefficients, more of them may collide, and multiple stages of sub-sampled DFTs are needed to deal with such collisions. In this paper, we propose a combinatorial aliasing-based SFT (CASFT) algorithm that is robust to noise and greatly reduces the number of stages by iteratively recovering coefficients. First, CASFT detects collisions and recovers coefficients via the CRT in a single stage. These coefficients are then subtracted from each stage, and the process iterates through the other stages. With a computational complexity of O(klog klog 2N) and sample complexity of O(klog 2N), CASFT is a novel and efficient SFT algorithm.

Strongly deterministic multithreading provides determinism for multithreaded programs even in the presence of data races. A common way to guarantee determinism for data races is to isolate threads by buffering shared memory accesses. Unfortunately, buffering all shared accesses is prohibitively costly. We propose an approach called DRDet to efficiently make data races deterministic. DRDet leverages the insight that, instead of buffering all shared memory accesses, it is sufficient to only buffer memory accesses involving data races. DRDet uses a sound data-race detector to detect all potential data races. These potential data races, along with all accesses which may access the same set of memory objects, are flagged as data-race-involved accesses. Unsurprisingly, the imprecision of static analyses makes a large fraction of shared accesses to be data-race-involved. DRDet employs two optimizations which aim at reducing the number of accesses to be sent to query alias analysis. We implement DRDet on CoreDet, a state-of-the-art deterministic multithreading system. Our empirical evaluation shows that DRDet reduces the overhead of CoreDet by an average of 1.6X, without weakening determinism and scalability.

Earlier attempts to deploy two units of parametric loudspeakers have shown encouraging results in improving the accuracy of spatial audio reproductions. As compared to a pair of conventional loudspeakers, this improvement is mainly a result of being free of crosstalk due to the sharp directivity of the parametric loudspeaker. By replacing the normal parametric loudspeaker with the steerable parametric loudspeaker, a flexible sweet spot can be created that tolerates head movements of the listener. However, spatial aliasing effects of the primary frequency waves are always observed in the steerable parametric loudspeaker. We are motivated to make use of the spatial aliasing effects to create two sound beams from one unit of the steerable parametric loudspeaker. Hence, a reduction of power consumption and physical size can be achieved by cutting down the number of loudspeakers used in an audio system. By introducing a new parameter, namely the relative steering angle, we propose a stereophonic beamsteering method that can control the amplitude difference corresponding to the interaural level difference (ILD) between two sound beams. Currently, this proposed method does not support the reproduction of interaural time differences (ITD).

We find necessary and sufficient conditions for the (shifted) oversampling expansions to hold in wavelet subspaces. In particular, we characterize scaling functions with the (shifted) oversampling property. We also obtain L2 and L∞ norm estimates for the truncation and aliasing errors of the oversampling expansion.

Compared with previous standards, H.264/AVC adopts variable block size motion estimation (VBSME) and multiple reference frames (MRF) to improve the video quality. Full search motion estimation algorithm (FS), which calculates every search candidate in the search window for 7 block type with multiple reference frames, consumes massive computation power. Mathematical analysis reveals that the aliasing problem of subsampling algorithm comes from high frequency signal components. Moreover, high frequency signal components are also the main issues that make MRF algorithm essential. As we know, a picture being rich of texture must contain lots of high frequency signals. So based on these mathematical investigations, two fast VBSME algorithms are proposed in this paper, namely edge block detection based subsampling method and motion vector based MRF early termination algorithm. Experiments show that strong correlation exists among the motion vectors of those blocks belonging to the same macroblock. Through exploiting this feature, a dynamically adjustment of the search ranges of integer motion estimation is proposed in this paper. Combing our proposed algorithms with UMHS almost saves 96-98% Integer Motion Estimation (IME) time compared to the exhaustive search algorithm. The induced coding quality loss is less than 0.8% bitrate increase or 0.04 dB PSNR decline on average.

Although the Digital Rights Management (DRM) systems have been rapidly developed to protect copyrights, they have not considered user privacy because they regard this as an unnecessary element in achieving their goals. However, the protection of user privacy becomes one of the most important issues in DRM systems as the number of people who suffer from accidents caused by the infringement of individual information dramatically increases. This paper suggests a license management protocol which is a more powerful protocol to protect individual information in DRM. To protect the exposure of information of user identification, the proposed protocol uses alias like a TID and a token instead of the identity of content users. Due to using alias, this protocol can guarantee the anonymity of content users. Also, it can prevent the leakage of individual information through encryption of usage information. In this way, it can protect the privacy of content users.

In texture mapping, anisotropic filtering methods, which require more texels, have been proposed for high-quality images. Memory bandwidth, however, is still limited by a bottleneck in the texture-filtering hardware. In this paper, we propose anisotropic texture filtering based on edge function. In generating the weight that plays a key role in filtering texels loaded from memory, the edge function gives accurate contribution of texels to the pixel intensity. The quality of images is superior to other methods. For images of the same quality, our method requires less than half the texels of other methods. In other words, the improvement in performance is more than twice that of other methods.

In this paper, a fragment-processing solution in 3D graphics rendering algorithms based on fragment lists (i.e. A-buffer) for minimizing loss of image quality is described. While all fragment information should be preserved for exact hidden surface removal, this places additional strain on hardware in terms of silicon gates and clock cycles. Therefore, we propose a fragment processing technique that can effectively merge fragments in order to decrease the depth of fragment lists. It renders scenes quite accurately even in the case when three fragments intersect each other. This algorithm improves hardware acceleration without deteriorating image quality.

Adapting to the structure of 2-D H-Transform, this paper proposes a novel wavelet domain half-pixel motion compensation algorithm HMRME (Half-pixel Multi-Resolution Motion Estimation). The primary objective of this study is the reduction of the aliasing effect caused by the down-sampling in the wavelet transform under the complexity constraints. The conventional multi-resolution motion estimation scheme can be combined with the half-pixel interpolation method to generate a new high-performance wavelet video codec. The preliminary results show that the performance of HMRME rises above its counterparts, the Multi-Resolution Motion Estimation (MRME) and the Adaptive Multi-Resolution Motion Estimation (AMRME).

For checkpointing to be practical, it has to introduce low overhead for the targeted application. As a means of reducing the overhead of checkpointing, this paper proposes a probabilistic checkpointing method, which uses block encoding to detect the modified memory area between two consecutive checkpoints. Since the proposed technique uses block encoding to detect the modified area, the possibility of aliasing exists in encoded words. However, this paper shows that the aliasing probability is near zero when an 8-byte encoded word is used. The performance of the proposed technique is analyzed and measured by using experiments. An analytic model which predicts the checkpointing overhead is first constructed. By using this model, the block size that produces the best performance for a given target program is estimated. In most cases, medium block sizes, i.e., 128 or 256 bytes, show the best performance. The proposed technique has also been implemented on Unix based systems, and its performance has been measured in real environments. According to the experimental results, the proposed technique reduces the overhead by 11.7% in the best case and increases the overhead by 0.5% in the worst case in comparison with page-based incremental checkpointing.

In this paper, we propose the multirate repeating method for alias free subband adaptive filters (AFSAFs) and consider its convergence property. It is shown that we can adjust the convergence speed and the final error of the adaptive filters by varying its two parameters according to the requirements of the applications where the method is applied. The proposed method has two parameters, namely, the number of channel and the number of repetition. We show that by increasing the number of channels we can reduce the final error, and this property is preferred when the signal-to-noise ratio (SNR) is low. On the other hand, we show that the convergence speed of the AFSAF approaches to that of the affine projection algorithm (APA) by increasing the number of repetition. Through the computer simulations, we show the effect of the proposed method.

Antialiased is one of challenging problems to be solved for the high fidelity image synthesis in 3D graphics. In this paper a rasterization processor which is capable of single-pass full-screen antialiasing is presented. To implement a H/W accelerated single-pass antialiased rasterization processor at the reasonable H/W cost and minimized processing performance degradation, our work is mainly focused on the efficient H/W implementation of a modified version of the A-buffer algorithm. For the efficient handling of partial-pixel fragments of the rasterization phase, a new partial-pixel-merging scheme and a simple and efficient new dynamic memory management scheme are proposed. For the final blending of partial-pixels without loss of generality, a parallel subpixel blender is introduced. To study the feasibility of the proposed rasterization processor as a practical rasterization processor, a prototype processor has been designed using a 0.35 µm EML technology. It operates 100 MHz @3.3 V and has the rendering performance from 25M to 80M pixel-fragments/sec depending on the scene complexity.

This paper proposes higher-order spread spectrum direct optical switching CDMA system and an aliasing canceler to remove the aliasing distortion caused by higher-order bandpass sampling. Theoretical analysis of the signal quality shows that the 3rd order bandpass sampling scheme can improve the carrier-to-interference-power ratio compared with the conventional 1st order bandpass sampling scheme, by 5 dB.

Following our former works on regular sampling in wavelet subspaces, the paper provides two algorithms to estimate the truncation error and aliasing error respectively when the theorem is applied to calculate concrete signals. Furthermore the shift sampling case is also discussed. Finally some important examples are calculated to show the algorithm.

The coming information society will require images at the high end of the quality range. By using a new method which focuses on the assessment words of the high order sensation, we are investigating the important physical factors for the difficult reproduction of high level, high quality sensation in the electronic capture and display of images. We have found a key assessment word "image depth" that describes appropriately the high order subjective sensation that is indispensable for the display of extra high quality images. Related to the depth of images, we have discovered a new physical factor and the degree of precision required of already known physical factors for the display of extra high quality images. The cross modulation among R, G and B signals is the newly discovered important physical factor affecting the quality of an electronic display. In addition, we have found that very strict control of distortion in the gamma and the step response and the strict suppression of the halation in a CRT display are necessary. We note that aliasing of the displayed images also destroys the sensation of depth. This paper first outlines the overall objective of our work, second considers the important physical factors as important for extra high quality imaging, and then describes the specific effects of cross modulation distortion, gamma, step response, halation and aliasing as they relate to image depth. Finally, the relation of the discussed physical factors with the high order sensation are discussed broadly.

This paper presents a new architecture for multiple-input signature analyzers. The proposed signature analyzer with Hδ inputs is designed by parallelizing a GLFSR(δ,m), where δ is the number of input signals and m is the number of stages in the feedback shift register. The GLFSR, developed by Pradhan and Gupta, is a general framework for representing LFSR-based signature analyzers. The parallelization technique described in this paper can be applied to any kind of GLFSR signature analyzer, e. g. , SISRs, MISRs, multiple MISRs and MLFSRs. It is shown that a proposed signature analyzer with Hδ inputs requires less complex hardware than either single GLFSR(Hδ,m)s or a parallel construction of the H original GLFSR(δ,m)s. It is also shown that the proposed signature analyzer, while requiring simpler hardware, has comparable aliasing probability with analyzers using conventional GLFSRs for some CUT error models of the same test response length and test time. The proposed technique would be practical for testing CUTs with a large number of output sequences, since the test circuit occupies a smaller area on the LSI chip than the conventional multiple-input signature analyzers of comparable aliasing probability.

An oversampling theorem for regular sampling in wavelet subspaces is established. The sufficient-necessary condition for which it holds is found. Meanwhile the truncation error and aliasing error are estimated respectively when the theorem is applied to reconstruct discretely sampled signals. Finally an algorithm is formulated and an example is calculated to show the algorithm.

In high performance compilers to process pointer-handling programs, precise pointer alias analysis is useful for the compilers to generate efficient object code. It is well known that most compiler techniques such as data flow analysis, dependence analysis, side effect analysis and optimizations are related to the alias problem. However, without data structure information, there is a limit on the precision of the alias analysis. Even though the automatic data structure detection problem is complex, when pointer manipulation satisfies some restrictions, some data structures can be detected automatically by compilers with some knowledge of aliases. In this paper, we propose an automatic data structure detection method for Pascal and Fortran 90. Linear list, tree and dag data structures are detected. Detected data structure information can be used not only for raising the precision of alias analysis but also for some optimizing techniques for pointer handling programs directly.

The aliasing probability was analyzed for MISRs when the error probability for each input was different. A closed form expression was derived by applying the complete weight distributions of linear codes over a Galois field and its dual codes. The aliasing probability for MISRs characterized by non-primitive polynomials was also analyzed. The inner product for binary representation of symbols was used instead of multiplication over a Galois field. The results show the perfect expression for analyzing the aliasing probability of MISRs.