Arbitrary Resampling Research Articles

FPGA implementation of an arbitrary resample rate, FOH, pulse width modulator

This study presents a field-programmable gate array implementation of an advanced pulse-width modulator which combines a first-order hold (FOH) with phase accumulator carrier pulse-width modulation (PACPWM) for significantly reduced phase delay, and bandwidth extension in multi-level applications. The FOH block supports arbitrary resampling rates and operates in a single clock cycle for simple integration into multi-rate or asynchronous systems. The proposed modulator is validated experimentally, with performance matching that predicted for both FOH and a zero-order hold (ZOH). For PWM with 8 kHz carrier frequency and 50.4 kHz resampling frequency, a 15 degree phase delay advantage is demonstrated for FOH compared with ZOH across the 5–10 kHz modulation band.

Efficient Parallelization of Polyphase Arbitrary Resampling FIR Filters for High-Speed Applications

This article describes a method for increasing the sampling rate of efficient polyphase arbitrary resampling FIR filters. An FPGA proof of concept prototype of this architecture has been implemented in a Xilinx Kintex-7 FPGA which is able to convert the sampling rate of a signal from 500 MHz to 600 MHz. This article compares this new architecture with other best known efficient resampling architectures implemented on the same FPGA. The area usage on the FPGA shows that our proposed implementation is very proficient in high bandwidth applications without requiring significantly more resources on the FPGA. A theoretical calculation of the resampling error introduced on a modulated data stream is provided to evaluate the new architecture against other existing resampling architectures.

Optimization of Evidence Analysis Cost Using Arbitrary Re-Sampling Techniques for Sample Influx into Forensic Science Laboratory

This study analyzes the sample influx (samples per case file) into forensic science laboratory (FSL) and the corresponding analysis costs and uses arbitrary re-sampling plans to establish the minimum cost function. The demand for forensic analysis increased for all disciplines, especially biology/DNA between 2014 and 2015. While the average distribution of case files was about 42.5%, 40.6% and 17% for the three disciplines, the distribution of samples was rather different being 12%, 82.5% and 5.5% for samples requiring forensic biology, chemistry and toxicology analysis, respectively. Results show that most of the analysis workload was on forensic chemistry analysis. The cost of analysis for case files and the corresponding sample influx varied in the ratio of 35:6:1 and 28:12:1 for forensic chemistry, biology/DNA and toxicology for year 2014 for 2015, respectively. In the two consecutive years, the cost for forensic chemistry analysis was comparatively very high, necessitating re-sampling. The time series of sample influx in all disciplines are strongly stochastic, with higher magnitude for chemistry, biology/DNA and toxicology, in this order. The PDFs of sample influx data are highly skewed to the right, especially forensic toxicology and biology/DNA with peaks at 1 and 3 samples per case file. The arbitrary re-sampling plans were best suited to forensic chemistry case files (where re-sampling conditions apply). The locus of arbitrary number of samples to take from the submitted forensic samples was used to establish the minimum and scientifically acceptable samples by applying minimization function developed in this paper. The cost minimization function was also developed based on the average cost per sample and choice of re-sampling plans depending on the range of sample influx, from which the savings were determined and maximized. Thus, the study gives a forensic scientist a business model and scientific decision making tool on minimum number of samples to analyze focusing on savings on analysis cost.

A Wideband Front-End Receiver Implementation on GPUs

Modern communication systems have frequency bands that are shared with multiple channels. A typical front-end transceiver is responsible for processing multiple channels simultaneously within the band. Although it is simpler to design a dedicated sub-transceiver for each channel, the overall cost of implementation is prohibitive. It is more desirable to design a single system that can process many channels at the same time. However, it is difficult to realize such a transceiver in wireless communication systems, since it needs to accommodate different standards, data rates, sampling rates, etc. In this paper, we address the challenges of flexible, cost-effective, multi-channel implementation of wideband receiver systems. In particular, we develop a novel implementation by applying graphics processing unit (GPU) technology to a wideband receiver that processes multiple channels at the same time, including channelization and arbitrary resampling. Our proposed new receiver architecture is flexible and reconfigurable via software, while providing high throughput and low latency.

Increasing the noise immunity of signal processing units of telecommunications on the basis of the modified synchronization schemes

The paper presents mathematical models formalizing analytical description of the synthesis filters polyphasic device synchronization signal processing blocks of telecommunications. A device synchronization of telecommunications using polyphasic and polyphase filters. The peculiarity of these schemes is that they contain only three multiplications. It was determined that the fractional change speeds when interpolation and decimation factors are low enough effective filters polyphasic interpolators Farrow, who can effectively arbitrary (irrational) resampling. A simulation scheme of information transmission channel using polyphase interpolation solutions. It is shown that this approach allows for structural synthesis device clock synchronization, enhance immunity signal processing blocks and get the advantage of the modified scheme for a given level of probability of bit errors. Experimentally, the use of cubic Lagrange interpolators in the circuit block synchronization signal processing with 16QAM (experimental conditions) allows you to gain at 1.4 dB for BER = 10-4, modified interpolation scheme and agreed multiphase filtering scheme allow you to gain at 3 dB for BER = 10-4 and modified interpolation device at 3.4 dB Performance interpolation device primarily for high values .

Cost Effective, Versatile, High Performance, Spectral Analysis in a Synthetic Instrument

This paper described a versatile block of signal conditioning options that process raw data samples from the A/D converter and deliver a filtered and resampled version of those data samples to a conventional FFT based spectrum analyzer. The conditioning performs a number of important processing functions. These include spectral translation to baseband, noise bandwidth reduction to signal bandwidth, and arbitrary resampling to obtain specified spectral spacing with available sized FFTs. The versatility of an FPGA based processor and signal conditioning block enables the use of the signal conditioner blocks to align sample rate with transform sizes without the need to vary input sample clock rate or the cut off bandwidth of analog anti-alias filters in the signal path. A straw man set of specifications for the spectrum analyzer was proposed and used as the basis of the simulations presented in this paper. The processing described here reflects the great versatility and flexibility available to the system designer. Broader bandwidths and greater dynamic range options can be quickly accommodated in the architecture presented here.

On the asymptotic accuracy of the bootstrap under arbitrary resampling size

We study the order of convergence of the Kolmogorov-Smirnov distance for the bootstrap of the mean and the bootstrap of quantiles when an arbitrary bootstrap sample size is used. We see that for the bootstrap of the mean, the best order of the bootstrap sample is of the order ofn, wheren is the sample size. In the case of non-lattice distributions and the bootstrap of the sample mean; the bootstrap removes the effect of the skewness of the distribution only when the bootstrap sample equals the sample size. However, for the bootstrap of quantiles, the preferred order of the bootstrap sample isn 2/3. For the bootstrap of quantiles, if the bootstrap sample is of ordern 2 or bigger, the bootstrap is not consistent.