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This project features a full-hardware sound compressor using the well known algorithm: IMA ADPCM. The core acts as a slave WISHBONE device. The output is perfectly compatible with any sound player with the IMA ADPCM codec (included by default in every Windows). Includes a testbench that takes an uncompressed PCM 16 bits Mono WAV file and outputs an IMA ADPCM compressed WAV file. Compression ratio is fixed for IMA-ADPCM, being 4:1. PLEASE NOTICE THAT THIS CORE IS LICENSED UNDER http://creativecommons.org/licenses/by-nc-sa/3.0/ (Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported). That means you may use it only for NON-COMMERCIAL purposes.
標(biāo)簽： full-hardware compressor algorithm features
上傳時間： 2014-01-14
上傳用戶：Shaikh
The FPGA can realize a more optimized Digital controller in DC/DC Converters when compare to DSPs. In this paper, based on the FPGA platform, The theoretical analysis, characteristics, simulation and design consideration are given. The methods to implement the digital DC/DC Converters have been researched. The function module, state machine of digital DC/DC controller and high resolution DPWM with Sigma- Delta dither has been introduced. They are verified by experiments on a 20 W, 300 KHz non-isolated synchronous buck converters.
標(biāo)簽： Converters controller optimized Digital
上傳時間： 2013-12-31
上傳用戶：tzl1975
This is a paper describing Pulse Compression technique implemented in the Weather Radar system. This paper presents data examples from the radars and contrasts the use of pulse compression waveforms with more traditional non-modulated pulsed waveforms.
標(biāo)簽： This Compression implemented describing
上傳時間： 2017-08-25
上傳用戶：問題問題
We introduce a sub-cell WENO reconstruction method to evaluate spatial derivatives in the high-order ADER scheme. The basic idea in our reconstruction is to use only r stencils to reconstruct the point-wise values of solutions and spatial derivatives for the 2r-1 th order ADER scheme in one dimension, while in two dimensions, the dimension-by-dimension sub-cell reconstruction approach for spatial derivatives is employed. Compared with the original ADER scheme of Toro and Titarev (2002) [2] that uses the direct derivatives of reconstructed polynomials for solutions to evaluate spatial derivatives, our method not only reduces greatly the computational costs of the ADER scheme on a given mesh, but also avoids possible numerical oscillations near discontinuities, as demonstrated by a number of one- and two-dimensional numerical tests. All these tests show that the 5th-order ADER scheme based on our sub-cell reconstruction method achieves the desired accuracy, and is essentially non-oscillatory and computationally cheaper for problems with discontinuities.
標(biāo)簽： 高精度格式
上傳時間： 2016-01-13
上傳用戶：ccsdcczd
32feet.NET is a shared-source project to make personal area networking technologies such as Bluetooth, Infrared (IrDA) and more, easily accessible from .NET code. Supports desktop, mobile or embedded systems. 32feet.NET is free for commercial or non-commercial use. If you use the binaries you can just use the library as-is, if you make modifications to the source you need to include the 32feet.NET License.txt document and ensure the file headers are not modified/removed. The project currently consists of the following libraries:- Bluetooth IrDA Object Exchange Bluetooth support requires a device with either the Microsoft, Widcomm, BlueSoleil, or Stonestreet One Bluetopia Bluetooth stack. Requires .NET Compact Framework v3.5 or above and Windows CE.NET 4.2 or above, or .NET Framework v3.5 for desktop Windows XP, Vista, 7 and 8. A subset of functionality is available for Windows Phone 8 and Windows Embedded Handheld 8 in the InTheHand.Phone.Bluetooth.dll library.
上傳時間： 2016-07-06
上傳用戶：magister2016
Dynasty 350, 700 208/575 Volt Models W/Auto-Line Maxstar 350, 700 File: TIG (GTAW) Including Optional Cart And Cooler CE And Non-CE Models
標(biāo)簽： Dynasty Maxstar 350 700
上傳時間： 2017-03-11
上傳用戶：zosoong
ESP8266 AT指令手冊示例，物聯(lián)網(wǎng)使用廣泛，參考此文檔可進行快速開發(fā)。
標(biāo)簽： Non-OS 8266 ESP AT 指令
上傳時間： 2018-06-05
上傳用戶：dear920
Reconstruction- and example-based super-resolution (SR) methods are promising for restoring a high-resolution (HR) image from low-resolution (LR) image(s). Under large magnification, reconstruction-based methods usually fail to hallucinate visual details while example-based methods sometimes introduce unexpected details. Given a generic LR image, to reconstruct a photo-realistic SR image and to suppress artifacts in the reconstructed SR image, we introduce a multi-scale dictionary to a novel SR method that simultaneously integrates local and non-local priors. The local prior suppresses artifacts by using steering kernel regression to predict the target pixel from a small local area. The non-local prior enriches visual details by taking a weighted average of a large neighborhood as an estimate of the target pixel. Essentially, these two priors are complementary to each other. Experimental results demonstrate that the proposed method can produce high quality SR recovery both quantitatively and perceptually.
標(biāo)簽： Super-resolution Multi-scale Dictionary Single Image for
上傳時間： 2019-03-28
上傳用戶：fullout
Accurate pose estimation plays an important role in solution of simultaneous localization and mapping (SLAM) problem, required for many robotic applications. This paper presents a new approach called R-SLAM, primarily to overcome systematic and non-systematic odometry errors which are generally caused by uneven floors, unexpected objects on the floor or wheel-slippage due to skidding or fast turns.The hybrid approach presented here combines the strengths of feature based and grid based methods to produce globally consistent high resolution maps within various types of environments.
標(biāo)簽： localization environments challenging Resilient mapping R-SLAM and in
上傳時間： 2019-09-15
上傳用戶：zhudx2007
atlab code for Non-negative Factorization of the Occurrence Tensor from Financial Contracts https://arxiv.org/pdf/1612.03350.pdf,
標(biāo)簽： tensor_n
上傳時間： 2020-01-01
上傳用戶：dawn1818
蟲蟲下載站版權(quán)所有 京ICP備2021023401號-1
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