Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
CDB470XS-DC28

CDB470XS-DC28

Cirrus Logic

BOARD EVAL 2CH ADC/8CH DAC DSP

1

CDB8420

CDB8420

Cirrus Logic

EVALUATION BOARD FOR CS8420

1

CDB4270

CDB4270

Cirrus Logic

BOARD EVAL FOR CS4270 CODEC

3

CDB42L52

CDB42L52

Cirrus Logic

BOARD EVAL FOR CS42L52 CODEC

1

CRD1171-2

CRD1171-2

Cirrus Logic

EVAL BOARD EV2 CRD1171

0

CDB4271

CDB4271

Cirrus Logic

EVAL BOARD CS4271 STEREO CODEC

0

CDBWM7331-M-2

CDBWM7331-M-2

Cirrus Logic

EVAL BD - WM7331 EVAL BOARD (2PC

0

CDBWM8325-M-1

CDBWM8325-M-1

Cirrus Logic

EVAL BD - WM8325 MINI EVAL BOARD

0

CDBWM8758B-M-1

CDBWM8758B-M-1

Cirrus Logic

EVAL BD - WM8758B MINI EVAL BOAR

0

CDB6220-1

CDB6220-1

Cirrus Logic

EVAL BD-BASEBRD8994/8993/8958/89

0

CDBWM8940-M-1

CDBWM8940-M-1

Cirrus Logic

EVAL BD - WM8940 MINI EVAL BOARD

0

CDKWM8351-S-1

CDKWM8351-S-1

Cirrus Logic

KIT - WM8351 KIT CDB6143 MB DC

0

CDBWM8233-M-1

CDBWM8233-M-1

Cirrus Logic

EVAL BD - WM8233 MINI EVAL BOARD

0

CDB5460AU

CDB5460AU

Cirrus Logic

EVALUATION BOARD FOR CS5460A

0

CDBWM8224-M-1

CDBWM8224-M-1

Cirrus Logic

EVAL BD - WM8224 MINI EVAL BOARD

0

CDB4385A

CDB4385A

Cirrus Logic

EVAL BOARD 8CH DAC DSD D/B1

0

CDKWM8998-S-1

CDKWM8998-S-1

Cirrus Logic

KIT - WM8998 KIT (VEGAS) LOCHNAG

0

CDBWM8766-M-1

CDBWM8766-M-1

Cirrus Logic

EVAL BD - WM8766 MINI EVAL BOARD

0

CDB46L41-CSPK

CDB46L41-CSPK

Cirrus Logic

USB AUDIO STREAMING CODEC DEVELO

0

CDB6229-1

CDB6229-1

Cirrus Logic

EVAL BD - BASE BRD WM8948/8946/8

0

Evaluation and Demonstration Boards and Kits

Evaluation and Demonstration Boards and Kits are hardware platforms designed to facilitate the development, testing, and demonstration of electronic systems. They serve as critical tools for engineers and developers to prototype applications, validate designs, and accelerate time-to-market. These boards integrate processors, sensors, communication interfaces, and software ecosystems, enabling rapid experimentation across diverse industries such as IoT, automotive, and industrial automation.

TypeFunctional FeaturesApplication Examples
Microcontroller Development BoardsEmbedded CPUs, GPIOs, integrated peripheralsIoT devices, robotics
FPGA Evaluation BoardsReconfigurable logic, high-speed interfacesCommunication systems, AI accelerators
Sensor Expansion KitsMulti-sensor integration (temperature, motion, etc.)Smart agriculture, environmental monitoring
Wireless Communication ModulesBluetooth/Wi-Fi/LoRa protocols, antenna interfacesConnected healthcare, smart cities

Typical architecture includes: - Processing Units: Microcontrollers, FPGAs, or SoCs - Memory: RAM, Flash, EEPROM - Interfaces: USB, UART, SPI, I2C, Ethernet - Power Management: Regulators, battery connectors - Software Stack: SDKs, device drivers, IDEs Physical designs often feature standardized form factors (e.g., Arduino Uno, Raspberry Pi HATs) for modular expansion.

ParameterDescription
Processor Performance (MHz/GHz)Determines computational capability
Memory Capacity (RAM/Flash)Affects program complexity and data storage
Interface TypesDictates peripheral compatibility
Power Consumption (mW/MHz)Critical for battery-operated devices
Operating Temperature (-40 C to +85 C)Defines environmental durability

- Internet of Things (IoT): Smart home controllers, edge AI nodes - Automotive: ADAS sensor fusion platforms - Industrial Automation: PLC controllers, predictive maintenance systems - Consumer Electronics: Wearables, AR/VR prototypes

ManufacturerRepresentative Products
STMicroelectronicsSTM32 Nucleo Series, SensorTile Kit
IntelIntel Edison, Movidius Neural Compute Stick
XilinxZynq UltraScale+ MPSoC Evaluation Kit
ArduinoArduino MKR Series, Nano 33 IoT

Key considerations: 1. Match processor capabilities to application complexity 2. Verify interface compatibility with target peripherals 3. Assess software ecosystem maturity (e.g., ROS support) 4. Evaluate power budget requirements 5. Consider long-term availability and community support

- Growing adoption of RISC-V-based evaluation platforms - Integration of AI/ML accelerators in edge computing boards - Expansion of open-source hardware ecosystems - Increased focus on energy-efficient architectures for IoT - Standardization of form factors (e.g., SparkFun's Qwiic system)

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