Academic literature on the topic 'Digital Signal Processing'

A fast-digitizer data acquisition system recently installed at the neutron time-of-flight experiment nELBE, which is located at the superconducting electron accelerator ELBE of Forschungszentrum Dresden-Rossendorf, is tested with two different detector types. Preamplifier signals from a high-purity germanium detector are digitized, stored and finally processed. For a precise determination of the energy of the detected radiation, the moving-window deconvolution algorithm is used to compensate the ballistic deficit and different shaping algorithms are applied. The energy resolution is determined in an experiment with γ-rays from a 22Na source and is compared to the energy resolution achieved with analogously processed signals. On the other hand, signals from the photomultipliers of barium fluoride and plastic scintillation detectors are digitized. These signals have risetimes of a few nanoseconds only. The moment of interaction of the radiation with the detector is determined by methods of digital signal processing. Therefore, different timing algorithms are implemented and tested with data from an experiment at nELBE. The time resolutions achieved with these algorithms are compared to each other as well as to reference values coming from analog signal processing. In addition to these experiments, some properties of the digitizing hardware are measured and a program for the analysis of stored, digitized data is developed. The analysis of the signals shows that the energy resolution achieved with the 10-bit digitizer system used here is not competitive to a 14-bit peak-sensing ADC, although the ballistic deficit can be fully corrected. However, digital methods give better result in sub-ns timing than analog signal processing.

A fast-digitizer data acquisition system recently installed at the neutron time-of-flight experiment nELBE, which is located at the superconducting electron accelerator ELBE of Forschungszentrum Dresden-Rossendorf, is tested with two different detector types. Preamplifier signals from a high-purity germanium detector are digitized, stored and finally processed. For a precise determination of the energy of the detected radiation, the moving-window deconvolution algorithm is used to compensate the ballistic deficit and different shaping algorithms are applied. The energy resolution is determined in an experiment with γ-rays from a 22Na source and is compared to the energy resolution achieved with analogously processed signals. On the other hand, signals from the photomultipliers of barium fluoride and plastic scintillation detectors are digitized. These signals have risetimes of a few nanoseconds only. The moment of interaction of the radiation with the detector is determined by methods of digital signal processing. Therefore, different timing algorithms are implemented and tested with data from an experiment at nELBE. The time resolutions achieved with these algorithms are compared to each other as well as to reference values coming from analog signal processing. In addition to these experiments, some properties of the digitizing hardware are measured and a program for the analysis of stored, digitized data is developed. The analysis of the signals shows that the energy resolution achieved with the 10-bit digitizer system used here is not competitive to a 14-bit peak-sensing ADC, although the ballistic deficit can be fully corrected. However, digital methods give better result in sub-ns timing than analog signal processing.

Because of the increasing importance of signal processing in today's society, there is a need to easily experiment with new ways to process signals. Usually, fast-performing digital signal processing is done with special-purpose hardware that are difficult to develop for. GPUs pose an alternative for fast performing digital signal processing. The work in this thesis is an analysis and implementation of a GPU version of a digital signal processing chain provided by SAAB. Through an iterative process of development and testing, a final implementation was achieved. Two benchmarks, both comprised of 4.2 M test samples, were made to compare the CPU implementation with the GPU implementation. The benchmark was run on three different platforms: a desktop computer, a NVIDIA Jetson AGX Xavier and a NVIDIA Jetson TX2. The results show that the parallelized version can reach several magnitudes higher throughput than the CPU implementation.

In on-board processing satellite systems in which FDMA/SCPC access schemes are employed. transmultiplexers are required for the frequency demultiplexing of the SCPC signals. Digital techniques for the implementation of the transmultiplexer for such application were examined in this project. The signal processing in the transmultiplexer operations involved many parameters which could be optimized in order to reduce the hardware complexity whilst satisfying the level of performance required of the system. An approach for the assessment of the relationship between the various parameters and the system performance was devised. which allowed hardware requirement of practical system specifications to be estimated. For systems involving signals of different bandwidths a more flexible implementation of the trans multiplexer is required and two computationally efficient methods. the DFT convolution and analysis/synthesis filter bank. were investigated. These methods gave greater flexibility to the input frequency plan of the transmultiplexer. at the expense of increased computational requirements. Filters were then designed to exploit specific properties of the flexible transmultiplexer methods. resulting in considerable improvement in their efficiencies. Hardware implementation of the flexible transmultiplexer was considered and an efficient multi-processor architecture in combination with parallel processing software algorithms for the signal processing operations were designed. Finally. an experimental model of the payload for a land-mobile satellite system proposal. T -SAT. was constructed using general-purpose digital signal processors and the merits of the on-board processing architecture was demonstrated.

Low cost microprocessors and DSPs are optimized to perform arithmetic and logic operations on data having a xed size, typically 16,32 or 64 bit. On the other hand, their e ciency decreases when data shorter respect than their native wordlength are processed (more clock cycles per operation are required). Recently di erent solutions have been proposed to overcome this problem. Among those, the ones based on a main processor with a Recon gurable Unit used as hardware accelerator are the most interesting in terms of performance and exibility. Typically those architectures are similar to very small FPGA; they consist in arrays of Look-Up Tables (LUTs) interconnected by pass transistors networks. This work proposes a new Recon gurable Accelerator called ADAPTO (Adderbased Dynamic Architecture for Processing Tailored Operators). The main di erent between ADAPTO and the others Recon gurable Units proposed in literature is the reduced hardware complexity in terms of silicon area. This feature give the possibility to integrate ADAPTO in embedded low cost microprocessors and DSPs (Digital Signal Processors), in fact, for these kind of processors, the area occupation and therefore the cost is a very critical aspect. The ADAPTO Unit supports both hardware recon guration and instruction execution in the same processor clock cycle. These goals have been obtained with the multicontext approach using a recon gurable unit based on full adders, instead LUTs. As discussed in this work this choice allows to the multicontext technique a reduced wasting of hardware resources.

Thesis (M.S.)--West Virginia University, 1999.<br>Title from document title page. Document formatted into pages; contains vi, 110 p. : ill. (some col.) Includes abstract. Includes bibliographical references (p. 66-68).

Increased usage of electronic devices and the fast development of microprocessors has increased the usage of digital filters ahead of analog filters. Digital filters offer great benefits over analog filters in that they are inexpensive, they can be reprogrammed easily and they open up whole new range of possibilities when it comes to Internet of things. This thesis describes development of a program that can sample music from the computer's microphone input, filter it inside the program with user built filters and reconstruct the music to the computer's headphone output meaning that the music can be played from the speakers. All of this is to happen in real time. The program is developed for students studying at the department of ``Signals and Systems" and the program is supposed the be one of the educational tools to make sense of signals and filtering. The program works well and filters the sound with satisfying results. It is easy to create filters and filter the signal. Since it is music that is filtered constructing perfect filters with minimum ripple, minimum or linear phase is quite difficult to achieve. The program could be improved by improving the user interface, making the environment more interactive and less difficult to construct good filters. Some improvements could also be made to the implementation; as of now the program might run a bit slow on startup on slower computers.