nils-herrmann/clean_scirepeval huggingface dataset:
Multigrid embedding (MGE) image coding

In this work we describe a simple transform-coefficient sorting algorithm that enhances the performance of image compression techniques. We use multiresolution grids to localize significant pixels and send out pixel values using successive approximation. In the wavelet domain our method performs slightly better than SPIHT (in average 0.1 dB of PSNR). In the DCT domain our method outperforms the SPIHT-based method and the significant tree quantization method by 1 dB. Our approach breaks the dominant role played by the zero tree structure in image coding, and provides a low complexity solution to image compression.
Audio watermarking by time-scale modification

A new algorithm for audio watermarking is proposed. The basic idea of the algorithm is to change the length of the intervals between salient points of the audio signal to embed data. We propose several novel ideas for practical implementations that can be used by other watermarking schemes as well. The algorithm is robust to common audio processing operations e.g. MP3 lossy compression, low pass filtering, and time-scale modification. The watermarked signal has very high perceptual quality and is indistinguishable from the original signal.
Pulsed-OFDM Modulation for Ultrawideband Communications

In this paper, we describe a novel approach for reducing the power consumption and complexity of a multiband orthogonal frequency-division multiplexing (MB-OFDM) ultrawideband (UWB) system by applying ideas from pulsed UWB systems. The approach is quite general and applicable to many other systems. Unlike the MB-OFDM system, the enhancement that we propose uses pulses with duty cycles of less than 1 as the amplitude shaping pulse of orthogonal frequency-division multiplexing (OFDM) modulation. Pulsating OFDM symbols spread the spectrum of the modulated signals in the frequency domain, leading to a spreading gain that is equal to the inverse of the duty cycle of the pulsed subcarriers. We study the spectral characteristics of pulsed OFDM and the added degrees of diversity that it provides. We show that pulsed-OFDM signals can easily be generated by either upsampling an equivalent OFDM baseband signal with a reduced number of carriers or by replacing the digital-to-analog converter (DAC) of a normal MB-OFDM transmitter with a low-duty-cycle DAC. We establish that a pulsed-OFDM receiver can fully exploit the added diversity without using Rake receivers. It is shown that, while pulsed OFDM has superior or comparable performance to MB-OFDM in multipath fading channels, it also has intrinsic low-complexity and power consumption advantages compared with MB-OFDM. To establish this fact, we describe an example design for the IEEE 802.15.3a Standard and present full simulation results for the UWB indoor propagation channels provided by the IEEE 802.15.3a Standard activity committee.
Unified framework of source-channel-modulation coding in low power multimedia wireless communications

We study the problem of jointly optimizing source/channel/modulation coding to achieve a given quality of service while minimizing the total power consumption of mobiles. This paper emphasizes the design of a robust transmission framework in the context of a total power minimization scheme. We design a simple but efficient transmission scheme which is called multistage coded modulation that combines source/channel (S/C) coding and multirate modulation (MM). We then integrate into this scheme a complexity-scalable video coder to achieve the best trade-offs in multimedia wireless communications between total power, quality of service, and capacity. Preliminary results show superior video frame quality (around 3 dB better than the simple S/C coding scheme) of the proposed system in the severe channel condition, with total power consumption kept to a minimum.
Multiresolution video watermarking using perceptual models and scene segmentation

We introduce a watermarking procedure to embed copyright protection into digital video. Our video dependent watermarking procedure directly exploits the masking and temporal properties to embed an invisible and robust watermark. The watermark consists of static and dynamic temporal components that are generated from a temporal wavelet transform of the video scenes. To generate the watermark, the resulting wavelet coefficient frames are modified by a perceptually shaped pseudo-random sequence representing the author. The noise-like watermark is statistically undetectable to thwart unauthorized removal. Furthermore, the author representation resolves the deadlock problem. The multiresolution watermark may be detected on single frames without knowledge of the location of the frames in the video scene. We demonstrate the robustness of the watermarking procedure to several video distortions.
Minimization of the spurious shot boundaries using principal components decomposition and progressive nonlinear filter

Shot boundary detection is an important for retrieval of visual media in multimedia systems. Video temporal segmentation algorithms use thresholding techniques to identify both abrupt shot changes and gradual shot transitions. Thresholding methods frequently provide false positives due to large variations in gradual transition regions. The principal component decomposition and progressive nonlinear filter (PNF) have been developed to suppress spurious temporal information in gradual transition regions while preserving abrupt shot changes. The spurious shot boundary information can be further minimized by a multistage shot boundary detection approach.
A deterministic blind identification technique for SIMO systems of unknown model order

In this paper we present a method for the deterministic blind identification of single-input multiple-output systems with unknown model order. The technique, that is applicable to both the FIR and IIR cases, requires only an upper bound of the model order. It is based on the special kernel structure of block Toeplitz matrices. When the model order is overestimated, this special structure entails the true solution to be embedded in the overestimated solution in a unique shift-chain form. This special shift-chain structure is then utilized to extract the true solution.
Packet loss recovery hybrid scheme for image multicast applications

In real-time multicast communication scalability, reliability, feedback implosion, and packet loss recovery are of paramount importance. In this work we have developed an efficient feedback-free, entirely receiver-driven, and reliable visual information delivery hybrid scheme (SIGMA-EC) for multicast applications over unreliable communication networks, that requires no per-receiver status at the sender. Our scheme's encoding and decoding processing time is an order of magnitude faster than conventional FEC-based loss recovery schemes. Among other attractive features, the reconstructed image quality gets progressively better. Furthermore, we obtain all these advantages using a remarkably simple structure, both conceptually as well as computationally.
On the application of uniform linear array bearing estimation techniques to uniform circular array

The problem of estimating the directions of arrivals of narrowband plane waves impinging on a uniform circular array with M identical sensors uniformly distributed around a circle is considered. It is shown that root MUSIC and other estimation algorithms which were designed to work with linear arrays can be applied to a circular array. Simulation experiments were conducted to compare the results of applying root MUSIC, MUSIC, and minimum norm to the transformed outputs of a 23-element circular array of radius 5 lambda /2 pi with those that are obtained by applying MUSIC and minimum norm to the array outputs directly.<<ETX>>
Unsupervised color image segmentation for content based application

We present an efficient unsupervised color image segmentation algorithm by combining the local and global color information. By first processing a color image via the proposed color sigma filter, pixels within the same semantic region become more concentrated around their centroid in the perceptual color coordinate system. A k-mean algorithm is then designed to automatically distinguish the image into non-overlapping semantic regions, of which centroids with similar color features are merged automatically. Because of the periodicity in the hue component, we apply two manifolds to completely cover the hue vector, and fuse distinguished regions from both manifolds to obtain the final image segmentation. The computational complexity of our algorithm is O(N), where N is the total number of pixels, and no priori information is assumed. We download sample images from the Internet randomly and apply the proposed algorithm to illustrate the performance of our procedure.
Waveform selection in radar target classification

We apply a sequential experiment design procedure to the problem of signal selection for radar target classification. Radar waveforms are designed to discriminate between targets possessing a doubly spread reflectivity function that are observed in clutter. The waveforms minimize decision time by maximizing the discrimination information in the echo signal. Each waveform selected maximizes the Kullback-Leibler (1951) information number that measures the dissimilarity between the observed target and the alternative targets. We discuss in details two scenarios. In the first scenario, the target environment is assumed fixed during illumination. In this case, the optimal waveform selection strategy leads to a fixed library of waveforms. During actual classification, the sequence in which the waveforms are selected from the library is determined from the noise to clutter power in the range-Doppler support of the targets. In the second scenario, the target environment changes between pulse transmissions. In this case, the maximum discrimination information is obtained by a repeated transmission of a single waveform designed from the reflectivity function of the targets. We show that our choice of signals can produce significant gains in detection performance.
Subband coding of binary textual images for document retrieval

Efficient compression of binary textual images is very important for applications such as document archiving and retrieval, digital libraries and facsimile. The basic property of a textual image is the repetitions of small character images and curves inside the document. Exploiting the redundancy of these repetitions is the key step in most of the coding algorithms. We use a similar compression method in the subband domain. Four different subband decomposition schemes are described and their performance on a textual image compression algorithm is examined. Experimentally, it is found that the described methods accomplish high compression ratios and they are suitable for fast database access and keyword search.
Pilot assisted multi-user UWB communications

In this paper, we study the use of sub-carrier pilots for multi-carrier ultra wideband (MC-UWB) systems. In particular, we introduce a simple receiver structure for sub-carrier pilot assisted ultra wideband orthogonal frequency division multiplexing (SPA-UWB-OFDM) system. The new system exploits the high time resolution of the UWB-OFDM signal to simplify the implementation of the full multipath diversity receivers. We show that any sub-carrier can be used to estimate the delays and complex amplitudes of the channel. Furthermore we show that if some of sub-carriers are modulated with training data, a generalized maximum likelihood ratio test (GMLRT) can be used to simultaneously estimate the channel and decode the transmitted information. The demodulation is done by correlating the information bearing sub-carriers with the pilot sub-carriers. Furthermore, we show that multi-user detection can be achieved by using different pilot sub-carriers for different users.
Data embedding in audio: where do we stand

Data embedding algorithms embed binary streams in host multimedia signals. The embedded data can add features to the host multimedia signal or provide copyright protection. We review requirements for transparent data embedding techniques in audio signals. We describe and contrast current approaches to data embedding in audio. In particular, we emphasize the advantages and limitations of the various approaches. We also describe possible signal processing and protocol level attacks on audio watermarking algorithms. We conclude with a discussion of future research directions.
Cube decoding

A novel lattice decoder called the cube decoder (CD) is proposed in this paper. The cube decoder finds the nearest lattice point to the received signal vector inside a hypercube centered at the received vector. The dimensions of the hypercube depends on the modulating lattice. This is achieved by reformulating the detection problem as a bounded-error subset selection (BESS) and solving a binary integer program. In this paper, it is assumed that the channel is known to the receiver. The proposed decoder uses the lattice reduction technique to reduce the interference introduced by the channel. Simulation shows that the CD gives near-optimal performance. Unlike the sphere decoder (SD), the complexity of the CD shows weak dependence on SNR.
Prediction of pharmacologically induced baroreflex sensitivity from noninvasive baroreflex, heart rate and systolic blood pressure variability indices

Assessment of baroreflex sensitivity (BRS) using vasoactive drugs is widely accepted in clinical research. It has been reported that decrease in BRS is an indicative of increased risk of sudden cardiac death. Due to its clinical importance, alternative baroreflex assessment methods have been developed which eliminate use of drugs and since then they are called non-invasive methods. In this study BRS index obtained by drug based assessment was predicted from subset of noninvasive BRS indices extracted from heart rate and systolic pressure time serieis. A leave one out method was employed to search subset of indices which gvies the highest correlation with invasive and predicted BRS. Two predictors provided the highest correlation (0.87). The algorithm selected consistently normalized cross-power in Mayer frequency band and average magnitude square coherence in high frequency band as predictors for all 16 subjects.
Biological significance of a novel biclustering technique on genetic expression data

Unlocking the complexity of a living organism's biological processes, functions, and genetic network is vital in learning how to improve the health of humankind. Genetic analysis, especially biclustering, is a significant step in this process. Learning how genes function together in groups, how they regulate under different conditions, and what proteins created by genes trigger certain biological processes will pave new pathways for genetic engineering and disease therapy. This experiment analyzes one such biclustering technique that combs over a gene expression matrix to find subgroups of genes with coherent evolution, that is genes whose expression levels stay constant or increase coherently over a subgroup of conditions or samples. This biclustering technique was applied to an S. cervisiae, or yeast, genetic expression data matrix. The biclustering was again performed on the same initial matrix two more times, each with selected genes omitted with the intent to increase the biological correlation relationship of the genes in the resultant biclusters. The final results were analyzed using a categorized system of known protein functional annotation from the yeast genome to find the biological significance of the submatrices detected by the algorithm
Modeling techniques for multiscale difference equation signal models

In this paper, we describe novel encoding and decoding methods for multiscale difference equation (MSDE) signal models. Recently, MSDE signal models have been introduced to exploit self-similarities in signals. The encoding process for MSDE models requires an adaptive signal representation from the dictionary of translations and dilations of the signal to be modeled. Here, we propose a new iterative technique that tries to select an 'active' set under the modeling constraints so that the portion of the signal representation due to the 'inactive' set has small or zero norm. Using methods similar to 'line searches and backtracking' used for global non-linear optimization, this method yields the global minima for exact representation. The decoding process involves an eigenvector analysis of a particular matrix. We provide a fast algorithm to obtain the required eigenvector in O(N/sup 2/ log N) operations. We also provide a perturbation analysis of MSDE models that gives a bound on the reconstruction error due to errors in the MSDE coefficients.
Software defined cognitive radios

The wide proliferation of wireless services and applications with increasing bandwidth needs is rapidly creating a spectrum shortage. However, the problem is caused primarily by inefficient legacy spectrum allocation policies, so that even when some applications suffer from lack of bandwidth, there is idle capacity in other bands. To deal with this challenge, the FCC, ITU and other regulatory organizations have begun to explore an open spectrum policy implemented by programmable wireless networks. Such wireless networks use cognitive, software reconfigurable radios to increase the efficiency of spectrum access. In particular such programmable wireless networks maximize the availability and enhance the quality of service of diverse applications using the most appropriate access network, or an aggregation of such networks, for any given local conditions. A software defined radio (SDR) terminal is essentially a reconfigurable system that can be dynamically programmed in software to reconfigure the characteristics of the hardware through the use of clearly defined APIs residing on top of a flexible hardware layer. The SDRs use different types of hardware to accomplish various communication tasks. In addition to the grammability and flexibility provided by the DSPs and software-driven communication parameters such as modulation, medium access, cryptography, etc, software defined radios also provide field service capability. So, when requirements change, code downloads, upgrades and modifications are relatively easy to execute. Ultimately, the success of the programmable wireless network vision will hinge on its ability to meet the high level needs of users, service providers, network operators and hardware and software developers. Ubiquitous access to applications with proper quality levels, low cost services, user friendliness, fast and open service creation, lifetime and flexibility of equipment, common execution environment, fast product design and manufacturing, to mention a few, translate into well defined technology requirements. In this tutorial we will discuss system, circuit and implementation issues necessary to design a programmable wireless network that meets these requirements.
Polynomial Time and Stack Decoding Solutions to Bounded Error Subset Selection

The goal of bounded error subset selection (BESS) is to find the sparsest representation of an Ntimes1 vector b using vectors from a dictionary A of size NtimesM, such that the approximation is within a distance delta from b. Here delta is a user defined approximation threshold. Specifically, the goal is to find the sparsest vector x such that parAx - bpar les delta. The BESS is a reformulation of the classical subset selection problem. We describe two enumeration approaches with bounded complexities that find the optimal solution to the BESS problem. In particular, the paper describes the first exhaustive enumeration solution to subset selection type problems with polynomial complexity. Furthermore, it also describes a lower complexity stack decoding approach that finds a solution to the BESS problem with a complexity that is proportional to that of orthogonal matching pursuit. The approaches described here have a markedly better rate-distortion behavior than any of the other known solutions to the subset selection and BESS problems
Image coding by folding

We propose an image coding algorithm which employs data hiding techniques to "fold" an image into itself. Data hiding is a process of encoding extra information into a host image by making small modifications to its pixels. In our approach, an image is split into two parts of equal size: a host image and a residual image. The residual image is compressed into a bit stream and then embedded into the host image. The host image, which is 50% of the size of the original image, is coded using standard compression techniques. The embedded data does not increase the bit rate of the coded image. As a result, one may code only 50% pixels of the original image and still have perfect reconstruction. Experimental results indicate that the algorithm has a lot of potential in image coding.
Toward accurate modeling of the IEEE 802.11e EDCA under finite load and error-prone channel

In this paper we study the performance of IEEE 802.11e enhanced distributed channel access (EDCA) priority schemes under finite load and error-prone channel. We introduce a multi-dimensional Markov Chain model that includes all the mandatory differentiation mechanisms of the standard: QoS parameters, CWMIN, CWMAX arbitration inter-frame space (AIFS), and the virtual collision handler. The model faithfully represents the functionality of the EDCA access mechanisms, including lesser known details of the standard such as the management of the backoff counter which is technically different from the one used in the legacy DCF. We study the priority schemes under both finite load and saturation conditions. Our analysis also takes into consideration channel conditions.
Embedded object dictionaries for image database browsing and searching

We describe a technique to encode images for content-based access and retrieval. Potential query terms are first extracted from an image and represented in terms of multiresolution subbands. A vector quantizer structure then maps the subbands of each image object onto a set of embedded dictionaries. An algorithm is used to exploit the occurrence and query probabilities of the objects for efficient coding and retrieval. Furthermore, a new browsing tool based on multiresolution prototypes is proposed. A prototype object is associated with each dictionary entry. Prototype objects may be substituted for subband data for high quality image browsing during retrieval.