Illustrates how to generate HDL code for a Digital Up-Converter (DUC). A DUC is a digital circuit which converts a digital baseband signal to a passband signal. The input baseband signal is
Design and implement hardware efficient Sample Rate Converters for an arbitrary factor using polynomial-based (Farrow) structures. Sample Rate Conversion (SRC) between arbitrary
Illustrates how to generate HDL code for a 5th order Butterworth filter. The cutoff-frequency for this filter is very low relative to the sample rate, leading to a filter that is difficult to
Illustrates how to generate HDL code for a symmetrical FIR filter with fully parallel, fully serial, partly serial and cascade-serial architectures for a lowpass filter for an audio
Illustrates how to generate HDL code for an inverse sinc (sin x/x) peaking filter that adds preemphasis to compensate for the inherent sinc response of the digital-to-analog converter
Illustrates how to generate HDL code for an ITU-R BT.601 luma filter with 8-bit input data and 10-bit output data. This filter is a low-pass filter with a -3 dB point of 3.2 MHz with a 13.5 MHz
Illustrates how to generate HDL code for a fractional delay (Farrow) filter for timing recovery in a digital modem. A Farrow filter structure provides variable fractional delay for the
Illustrates how to generate HDL code for a minimum phase FIRT filter with 10-bit input data. This is a bandpass filter with sample rate of 96 kHz and passband from approximately 19 kHz to 29 kHz.
Illustrates how to generate HDL code for bank of 24 first-order shelving filters that implement an audio tone control with 1 dB steps from -6 dB to +6 dB for bass and treble.
Illustrates how to generate HDL code for a lowpass FIR filter with Distributed Arithmetic (DA) architecture.
Illustrates how to generate HDL code for an FIR filter with a processor interface for loading coefficients. The filter can be programmed to any desired response by loading the coefficients
Compute square root using a CORDIC kernel algorithm in MATLAB®. CORDIC-based algorithms are critical to many embedded applications, including motor controls, navigation, signal
Use the CORDIC algorithm, polynomial approximation, and lookup table approaches to calculate the fixed-point, four quadrant inverse tangent. These implementations are approximations
Convert a textbook version of the Fast Fourier Transform (FFT) algorithm into fixed-point MATLAB® code.
Use both CORDIC-based and lookup table-based algorithms provided by the Fixed-Point Designer™ to approximate the MATLAB® sine (SIN) and cosine (COS) functions. Efficient fixed-point
Accelerate fixed-point algorithms using fiaccel function. You generate a MEX function from MATLAB® code, run the generated MEX function, and compare the execution speed with MATLAB code
Convert a finite impulse-response (FIR) filter to fixed point by separating the fixed-point type specification from the algorithm code.
Define unsigned and signed two's complement integer and fixed-point numbers.
Write MATLAB® code that works for both floating-point and fixed-point data types. The algorithm used in this example is the QR factorization implemented via CORDIC (Coordinate Rotation
Compute sine and cosine using a CORDIC rotation kernel in MATLAB®. CORDIC-based algorithms are critical to many embedded applications, including motor controls, navigation, signal
Implement fixed-point square root using a lookup table. Lookup tables generate efficient code for embedded devices.
Convert Cartesian to polar coordinates using a CORDIC vectoring kernel algorithm in MATLAB®. CORDIC-based algorithms are critical to many embedded applications, including motor
Analyze a fixed-point state-space system to detect limit cycles.
Implement fixed-point log2 using a lookup table. Lookup tables generate efficient code for embedded devices.
Compute and compare the statistics of the signal quantization error when using various rounding methods.
Set fixed-point data types by instrumenting MATLAB® code for min/max logging and using the tools to propose data types.
This demo introduces user to the new and enhanced bitwise operators provided in Fixed Point toolbox in R2007b. These functions are supported by Embedded MATLAB block for both software and
Demonstrates code generation for an image classification application that uses deep learning. It uses the codegen command to generate a MEX function that runs prediction using popular
Demonstrates code generation for pedestrian detection application that uses deep learning. Pedestrian detection is a key problem in computer vision, with several applications in the
Generate CUDA® code from a deep learning network, which is represented by a SeriesNetwork object. The SeriesNetwork in this example is a convolutional neural network that can detect and
Demonstrates how to generate CUDA® MEX code for a traffic sign detection and recognition application, that uses deep learning. Traffic sign detection and recognition is an important
Generate CUDA® code from a SeriesNetwork object created for YOLO architecture trained for classifying the PASCAL dataset. YOLO is an object detection network that can classify objects in
Demonstrates code generation for a logo classification application that uses deep learning. It uses the codegen command to generate a MEX function that runs prediction on a SeriesNetwork
Generate a MEX function from a MATLAB function that computes the stereo disparity of two images.
Generate CUDA® MEX from MATLAB® code and perform feature matching between two images. This example uses the matchFeatures function from the Image Processing Toolbox™ to match the feature
Object Recognition using Speeded-Up Robust Features (SURF) is composed of three steps - feature extraction, feature description, and feature matching. This example performs feature
Demonstrates the use of image processing functions for GPU Code generation. The example takes a foggy image as input and produces a defogged image. This is a typical implementation of fog
Generate CUDA® kernels for stencil type operations by implementing John H. Conway's "Game of Life".
Demonstrates how to use GPU Coder™ to leverage the CUDA® Fast Fourier Transform library (cuFFT) and compute two-dimensional FFT on a NVIDIA® GPU. The two-dimensional Fourier transform is
Looks at how we can benchmark the solving of a linear system by generating GPU code. The MATLAB® code to solve for x in A*x = b is very simple. Most frequently, we use matrix left division, also
Generate CUDA® code from a simple MATLAB® function by using GPU Coder™. A Mandelbrot set implementation by using standard MATLAB commands acts as the entry-point function. This example
Integrate GPU Coder™ into Simulink®. While GPU Coder is not supported for Simulink blocks, you can still leverage GPUs in Simulink by generating a dynamic linked library (dll) using GPU
Generate CUDA® code from a SeriesNetwork object and target the NVIDIA's TX2 board with an external camera. This example uses the AlexNet deep learning network to classify images from a USB
Generate HDL code from a MATLAB® design that does image enhancement using histogram equalization.
Use the HDL Coder™ to generate a custom HDL IP core which blinks LEDs on the Arrow® SoCKit® evaluation kit, and shows how to use Embedded Coder® to generate C code that runs on the ARM® processor
HDL code generation from a floating-point MATLAB® design that is not ready for code generation in two steps. First we use float2fixed conversion process to generate a lookup table based
Generate HDL code from a MATLAB® design that implements an LMS filter. It also shows how to design a testbench that implements noise cancellation using this filter.
Use MATLAB® HDL Workflow Advisor to generate a custom HDL IP core which blinks LEDs on FPGA board. The generated IP core can be used on Xilinx® Zynq® platform, or on any Xilinx FPGA with
Generate HDL code from a MATLAB® design implementing the adaptive median filter algorithm suited for HDL code generation.
Generate HDL code from MATLAB® design implementing an bisection algorithm to calculate the square root of a number in fixed point notation.
Use the HDL Coder™ to generate a custom HDL IP core which blinks LEDs on the Xilinx® Zynq® ZC702 evaluation kit, and shows how to use Embedded Coder® to generate C code that runs on the ARM®
Generate HDL code from a MATLAB® design implementing a RGB2YUV conversion.
Work with MATLAB® HDL Coder™ projects to generate HDL from MATLAB designs.
Perform a design-level area optimization in HDL Coder by converting constant multipliers into shifts and adds using canonical signed digit (CSD) techniques.
Generate modular HDL code from MATLAB® code containing functions.
Generate a MATLAB Function block from a MATLAB® design for system simulation, code generation, and FPGA programming in Simulink®.
Generate HDL code from MATLAB® code modeling transfer data between transmit and receive FIFO.
Debug a Zynq design using HDL Coder™ and Embedded Coder® features.
Generate HDL code from a MATLAB® design that adjusts image contrast by linearly scaling pixel values.
Start with a floating-point design in MATLAB, iteratively converge on an efficient fixed-point design in MATLAB, and verify the numerical accuracy of the generated fixed-point design.
Define and register a custom board and reference design in the HDL Coder™ SoC workflow. Using this example, you will be able to register the Digilent® Zybo Zynq™ development board and a custom
Generate HDL code from a MATLAB® design that implements a high dynamic range imaging algorithm.
Check, generate and verify HDL code from MATLAB® code that instantiates a non-restoring square root system object.
MATLAB code generation from a floating-point MATLAB® design that is not ready for code generation. We use 'coder.approximate' function to generate a lookup table based MATLAB function.
HDL code generation from a fixed-point MATLAB® design that is ready for code generation.
Generate a standalone C library from MATLAB code that implements a simple Sobel filter that performs edge detection on images. The example also shows how to generate and test a MEX function in
The recommended workflow for generating C code from a MATLAB function using the 'codegen' command. These are the steps: 1. Add the %#codegen directive to the MATLAB function to indicate that
Generate C code for a MATLAB Kalman filter function,'kalmanfilter', which estimates the position of a moving object based on past noisy measurements. It also shows how to generate a MEX
Generate a standalone C library from MATLAB code that reads a file from disk using the standard C functions fopen/fread/fclose. To call these C functions, the MATLAB code uses the
Generate a MEX function from a simple MATLAB function using the 'codegen' command. You can use 'codegen' to check that your MATLAB code is suitable for code generation and, in many cases, to
Generate a MEX function and C source code from MATLAB code that performs portfolio optimization using the Black Litterman approach.
These examples are using Einstein's General Relativity to calculate geodesics in curved space-time.
Use code replacement libraries to replace operators and functions in the generated code. The MATLAB code described illustrates the replacement capabilities. With each example MATLAB
Accelerate the execution of a MATLAB algorithm that uses MATLAB classes. The classes create a reverberation effect, that is, the "echo" you hear in a large empty room.
Write a MATLAB function that uses structure arrays so that it is suitable for code generation. For code generation, you must first create a scalar template version of the structure before
Generate a standalone C library from MATLAB code that applies a simple histogram equalization function to images to improve image contrast. The example uses parfor to process each of the
Generate code for a MATLAB algorithm that runs a simulation of bouncing "atoms" and returns the result after a number of iterations. There are no upper bounds on the number of atoms that the
Generate a MEX function from a MATLAB function, 'compute_average', that uses persistent variables. It illustrates that you must clear the state of persistent variables before using the
Accelerate MATLAB algorithm execution using a generated MEX function. It uses the 'codegen' command to generate a MEX function for a complicated application that uses multiple MATLAB
Register and use a toolchain to compile an executable. This example uses Intel® Compiler, but the concepts and API shown below can be used for any toolchain. The registered toolchain can be
Pack and unpack data using the provided packData and unpackData functions
This example shows how to generate code from packData and unpackData
Develop and use code replacement library entries for target-specific function implementations that require data to be aligned to optimize application performance. To configure data
Control whether structure arguments to generated entry-point functions are passed by reference or by value.
Generate code for a function that uses enumerated types. In this example, the enumerated types inherit from base type int32. The base type can be int8, uint8, int16, uint16, or int32.
Name the C structure type to use in code generated for a global structure.
Test the output of generated code by using MATLAB® unit tests with MATLAB® Coder™.