Autocorrelation is a widely used statistical tool for determining periodicity and the fundamental period of a time-series. Calculating the autocorrelation function R-xx(k), we cross-correlate the signal with itself in...
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ISBN:
(纸本)9781479959969
Autocorrelation is a widely used statistical tool for determining periodicity and the fundamental period of a time-series. Calculating the autocorrelation function R-xx(k), we cross-correlate the signal with itself in order to detect non-randomness or to find repeating patterns. A continuous output, autocorrelation algorithm is proposed here which is able to detect periodicity in motor behaviour of free-roaming animals. The data stream is coming from a 3-axis accelerometer mounted on a collar.
This paper presents a general variable step-size (VSS) adaptive filter. The variable step-size normalized least mean square (VSSNLMS) and VSS affine projection algorithms (VSSAPA) are particular examples of adaptive a...
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ISBN:
(纸本)9781479925810
This paper presents a general variable step-size (VSS) adaptive filter. The variable step-size normalized least mean square (VSSNLMS) and VSS affine projection algorithms (VSSAPA) are particular examples of adaptive algorithms covered by this generic adaptive filter. Then, a new VSS partial rank (VSSPR) adaptive filter algorithm based on the generic VSS adaptive filter is introduced for noise cancellation in speech enhancement. The proposed algorithm has faster convergence rate and lower steady state mean square error compare with ordinary PRA. The good performance of the new algorithm is demonstrated via simulation results in attenuating the noise.
Fast Fourier transform (FFT) implementation on the TMS320C66x multicore digital signal processor (DSP) from Texas Instruments is considered in this paper. A FFT parallelization strategy is chosen and an expected perfo...
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ISBN:
(纸本)9781479968435
Fast Fourier transform (FFT) implementation on the TMS320C66x multicore digital signal processor (DSP) from Texas Instruments is considered in this paper. A FFT parallelization strategy is chosen and an expected performance gain is estimated. The algorithm is implemented in software for a four-core DSP architecture with interactions between cores based on inter-processor communication (IPC) and open multi-processing (OpenMP) techniques. Experimental results for a performance gain dependent on transform size are given. 2.9 times processing time reduction with 4 cores implementation is achieved.
This paper introduces a novel Real-Time Operating System (RTOS) based on a parameterized dataflow Model of Computation (MoC). This RTOS, called Synchronous Parameterized and Interfaced Dataflow Embedded Runtime (SPiDE...
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ISBN:
(纸本)9781479968435
This paper introduces a novel Real-Time Operating System (RTOS) based on a parameterized dataflow Model of Computation (MoC). This RTOS, called Synchronous Parameterized and Interfaced Dataflow Embedded Runtime (SPiDER), aims at efficiently scheduling Parameterized and Interfaced Synchronous Dataflow (PiSDF) graphs on multicore architectures. It exploits features of PiSDF to locate locally static regions that exhibit predictable application behavior. This paper uses a multicore signal processing benchmark to demonstrate that the SPiDER runtime can exploit more parallelism than a conventional multicore task scheduler. By comparing experimental results of the SPiDER runtime on an 8-core Texas Instruments Keystone I Digital Signal Processor (DSP) with those obtained from the OpenMP framework, latency improvements of up to 26% are demonstrated.
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