| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Cirrus Logic |
KIT - WM8904 KIT CDB6201 8904DC |
0 |
|
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Cirrus Logic |
EVAL BD - WM8985 MINI EVAL BOARD |
0 |
|
|
Cirrus Logic |
KIT - WM8750BL KIT CDB6097 MB DC |
0 |
|
|
Cirrus Logic |
EVAL BD DAUGHTER CARD ATHENA4 |
0 |
|
|
Cirrus Logic |
WM8782-6125-SSOP20-EV1 |
0 |
|
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Cirrus Logic |
MODULE COBRANET 1810 CM2 MT |
0 |
|
|
Cirrus Logic |
EVAL BD - BASE BRD WM8988/8750/8 |
0 |
|
|
Cirrus Logic |
EVAL BD - DSP REF DESIGN DAGDA 3 |
0 |
|
|
Cirrus Logic |
EVAL BD - WM8988 MINI EVAL BOARD |
0 |
|
|
Cirrus Logic |
KIT - WM9712 KIT CDB6123 MB DC |
0 |
|
|
Cirrus Logic |
EVAL BD - DAUGHTER CARD FOR ATHE |
0 |
|
|
Cirrus Logic |
EVAL BD - WM8351 MINI EVAL BOARD |
0 |
|
|
Cirrus Logic |
KIT - WM8983 KIT CDB6160 MB DC |
0 |
|
|
Cirrus Logic |
EVAL BD - WM9712 MINI EVAL BOARD |
0 |
|
|
Cirrus Logic |
MODULE COBRANET 4961 CM2 MT |
0 |
|
|
Cirrus Logic |
BD-HIPFDACINTGHPDRVR&IMP DTC |
0 |
|
|
Cirrus Logic |
BOARD EVAL FOR CS5464 ADC |
0 |
|
|
Cirrus Logic |
EVAL BD - WM8255 MINI EVAL BOARD |
0 |
|
|
Cirrus Logic |
EVAL BD DSP DAUGHT CARD DAGDA3 |
0 |
|
|
Cirrus Logic |
MODULE COBRANET 1810 CM2 FB |
0 |
|
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.
| Type | Functional Features | Application Examples |
|---|---|---|
| Microcontroller Development Boards | Embedded CPUs, GPIOs, integrated peripherals | IoT devices, robotics |
| FPGA Evaluation Boards | Reconfigurable logic, high-speed interfaces | Communication systems, AI accelerators |
| Sensor Expansion Kits | Multi-sensor integration (temperature, motion, etc.) | Smart agriculture, environmental monitoring |
| Wireless Communication Modules | Bluetooth/Wi-Fi/LoRa protocols, antenna interfaces | Connected 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.
| Parameter | Description |
|---|---|
| Processor Performance (MHz/GHz) | Determines computational capability |
| Memory Capacity (RAM/Flash) | Affects program complexity and data storage |
| Interface Types | Dictates 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
| Manufacturer | Representative Products |
|---|---|
| STMicroelectronics | STM32 Nucleo Series, SensorTile Kit |
| Intel | Intel Edison, Movidius Neural Compute Stick |
| Xilinx | Zynq UltraScale+ MPSoC Evaluation Kit |
| Arduino | Arduino 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)